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    "textoCompleto" => "<p class="elsevierStylePara"><span class="elsevierStyleBold">INTRODUCTION</span></p><p class="elsevierStylePara">The publication of a series of articles in the January issue of the journal JAMA titled &#191;How to use an article about genetic association&#191;<span class="elsevierStyleSup">1-3</span> serves as an excellent starting point to try a two-fold purpose&#58; to present&#44; similarly to what has been published&#44;a practical guide with the necessary requirements to face an article on genetic association&#44; and&#44; on the other hand&#44; to show the necessary tools to perform such a study&#46; To the present purpose&#44; we reduce the scope of action to those works on population based genetic association that are carried out by recruiting cases and controls considering that we will be evaluating candidate genes&#46; Methods and interpretation of results from family-based genetic studies are different and are not within the scope of this revision&#46; We insist in that our intention is only to point out a series of practical application guidelines and not to attempt any approach to genetic epidemiology&#46; We will therefore draw some considerations over the clinical relevance of these studies and analyse the current situation and its survival against genome-wide association studies&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">ARE THE PATIENTS APPROPRIATELY SELECTED&#63; PHENOTYPIC CHARACTERISATION</span></p><p class="elsevierStylePara">The adequate characterisation of a phenotype associated with certain disease is to be done in compliance with those clinical criteria over which there is a clearly established medical-scientific agreement&#46; Most scientific societies set these criteria and&#44; of course&#44; their corresponding updates&#44; as knowledge about disease progression and evolution is enhanced&#46; In real terms&#44; however&#44; it is not always possible to establish the right phenotype even when the guideline criteria are rigorously followed&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">IS SAMPLE SIZE THE RIGHT ONE&#63;</span></p><p class="elsevierStylePara">Assessing sample size &#40;table 1&#41; in a case-control study that includes genetic information is an object of constant study and remodeling&#46;<span class="elsevierStyleSup">4</span> A usual approach to assessing the sample size in a genetic association study does not differ from one in a usual clinical exposed&#47;not exposed-type study&#44; and it is based on previously establishing the magnitude of the difference to detect&#46; In our particular case&#44; it would mean to establish a priori the difference between the allelic or genotypic frequency in our populations&#46; In addition&#44; we have to know the frequency of alleles &#40;all those to be considered&#41; in the control population&#44; the value of type I error&#44; i&#46;e&#46; the error of rejecting the null hypothesis when the null hypothesis is true&#44; and type II error&#44; that is accepting the null hypothesis when the null hypothesis is false&#46; We usually play safe as not to make type I error in 95&#37; &#40;probability&#44; &#945; &#61; 0&#46;05&#41; and 5 to 20&#37; type II&#59; although&#44; it is usually set at 20&#37; &#40;probability&#44; &#946; &#61; 0&#46;2&#41;&#46; Thus a statistical power &#40;1 - &#946;&#41; of 80&#37; is ensured&#46; Other aspects should be considered too&#44; such as predictable error rate and type of errors to be expected in our genotyping procedure&#44; which should be compensated by a larger sample size so as not to reduce the statistical power&#46; Some &#191;on-line&#191; tools that help us in these calculations are&#44; among others&#58; http&#58;&#47;&#47;linkage&#46;rockefeller&#46;edu&#47;pawe&#47; y http&#58;&#47;&#47;hydra&#46;usc&#46;edu&#47;GxE&#47;&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">DISCUSSION OVER THE CASES</span></p><p class="elsevierStylePara">Ideally&#44; incident cases should be recruited&#46; Knowing in advance the allelic frequency of the variants to be studied and before proceeding to recruiting phase&#44; and being aware of the difficulty inherent in a given phenotype&#44; the number of subjects &#40;cases&#41; to be studied could be increased through various alternatives&#58; on the one hand&#44; by increasing the number while being less demanding when defining the phenotype&#44; as for example in &#171;renal disease&#187;&#44; thus increasing heterogeneity and reducing certainty to allele causality under evaluation&#59; on the other hand&#44; phenotype selection criteria could be more rigorous&#44; thus increasing homogeneity but necessarily reducing the number of cases recruited&#46; Alternatively&#44; phase duration for recruitment could be increased&#46; Choosing one alternative depends on various factors&#44; mainly on the allelic frequency of the variation&#40;s&#41; in the candidate gene&#40;s&#41; to be studied&#46; If an open criterion is chosen to select the cases&#44; it is to be expected that the candidate genes are present in a lower sub-group of our cases to study&#59; therefore&#44; due to the smaller effect size expected we will at least lose part of the statistical power that we intended to attain when defining our phenotype more broadly&#46; Hence&#44; when it comes to defining the cases we have to consider whether incrementing the cases available compensates for the loss in statistical power derived from a smaller difference in the frequencies expected&#46; If we postpone defining the phenotype until the moment when we have performed the analysis of our results&#44; we have alternatives&#46; Some authors&#44; such as Chen and Lee&#44; have created a simple quantitative method that allows us to clarify and systematize&#44; depending on the allelic frequencies and the existence of at least two possible types of &#171;cases&#187;&#44; when we can increase or not the size of our sample by linking both case types&#46;<span class="elsevierStyleSup">5</span> Nevertheless&#44; it is most scientifically appropriate to act in advance of these questions at the design phase of the study and not when we proceed to perform the statistical analysis&#44; since we might over-adjust the data thus obtaining spurious results that are difficult to replicate&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">DISCUSSION OVER THE CONTROLS</span></p><p class="elsevierStylePara">Arya Sharma and Xavier Jeunemaitre&#44;<span class="elsevierStyleSup">6</span> authors of renown in this area&#44; point at a common difficulty and error in the selection and control population recruitment&#46; The difficulty stems from the very nature of the control population&#46; While for most of the hospital researchers the inclusion of patients has not been a problem&#44; control recruiting has&#44; as it requires a population basis with specific resources&#46; Given that a control is potentially a case&#44; a usual bias is to include controls from&#44; for example&#44; blood banks or healthy workers in the area&#46; Selecting these candidates defined as &#171;hyper normal&#187; would theoretically result in a major difference in allelic frequencies between the affected and the control population&#44; but the advantage to this is indeed minimal and it might hide other phenotypes of positive selection toward survival&#46;<span class="elsevierStyleSup">7-9</span> Likewise&#44; selecting controls that are not diagnosed cases entails a reduction in the statistic power of our study&#46;<span class="elsevierStyleSup">10</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">ON STATISTICAL ANALYSIS AND STATISTICAL ASSOCIATION</span></p><p class="elsevierStylePara">We can set a phenotype selection that has to be studied characterising the phenotype as a dichotomous trait&#58; diabetics against non-diabetics&#44; hypertensive against normotensive&#44; or by trying to further delimit variability by reducing environmental uncertainty and gaining in phenotype influence through the evaluation of so-called intermediate phenotypes&#44; i&#46;e&#46; by evaluating one or many measurable characters that linked by plausible biological pathways our candidate gene&#40;s&#41; to the disease&#46; The most conventional statistical approach to either one alternative implies carrying out multivariate models&#46;</p><p class="elsevierStylePara">In studies with multiple comparisons we have to use corrections to avoid increasing type I error &#40;table 2&#41;&#46; Bonferroni procedure consists in dividing alpha by the number of comparisons to estimate&#58; if there are approximately 106 variants in the genome&#44; the threshold value of p corrected for all the comparisons would be p &#61; 0&#46;05&#47;106 &#61; 5 X 10-8&#46; If we intend to detect moderate differences this forces us to have a large sample size&#46; For this reason&#44; less conservative correction formulas are used&#44; such as the False Discovery Rate&#46; However&#44; when making numerous comparisons even using this procedure requires increasing the sample size too much&#46;</p><p class="elsevierStylePara">The statistical analysis used may give us a major statistical power &#40;table 3&#41;&#46; Thus&#44; if we know the genetic model &#40;additive-recessive-dominant&#41;&#44; we should use the Cochran-Armitage test&#46; However&#44; in general we do not know the genetic model of our candidate genes&#44; and although it gives us more power&#44; it is also true that it turns out to be less robust than the traditional Pearson&#191;s chi-square test&#44; which is the reason why in case of non-compliance with the cases we set up over the genetic model the results would become invalidated&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">ANALYSIS OF POPULATION MIX</span></p><p class="elsevierStylePara">The need&#44; in medicine&#44; to evaluate genetic heterogeneity in the population under study derives from the current evolution theory&#46; The studies show that although there is variation of frequency between alleles associated with the disease between dissimilar populations&#44; this is indeed quite small&#46;<span class="elsevierStyleSup">7</span> It might be the case that the association depended wholly on the exposure to certain environmental determinant whose frequency varied according to geographic localization and that frequency of these alleles by selection varied accordingly&#46;<span class="elsevierStyleSup">7</span> When population mixes are made that differ in allelic frequencies because of genetic or environmental reasons the association may turn out to be spurious&#46; Therefore the need for selection&#44; genotyping&#44; and neutral markers analysis &#40;null alleles&#44; unlinked SNPs&#44; insertions&#47;deletions&#41; through two different strategies termed &#191;genomic control&#191; and &#191;structured association&#191;&#58; http&#58;&#47;&#47;pritch&#46;bsd&#46;uchicago&#46;edu&#47;structure&#46;html and http&#58;&#47;&#47;wpicr&#46;wpic&#46;pitt&#46;edu&#47;WPICCompGen&#47;genomic&#95;control&#47;genomic&#95;control&#46;htm</p><p class="elsevierStylePara"><span class="elsevierStyleBold">SELECTION OF CANDIDATE GENES</span></p><p class="elsevierStylePara">Since in our approach we have decided to evaluate gene polymorphisms in candidates genes&#44; we are interested&#44; firstly&#44; in determining both the number and what genes we analyse&#46; The candidate genes under analysis are traditionally selected based on of the knowledge about the following&#58; gene product activity in the disease under study&#44; function of the protein coded by such gene&#44; information on studies in animal models&#44; knowledge presupposed from the phenotype associated with monogenic forms of the disease&#44; knowledge derived from gene linkage studies&#44; and data available a priori&#44; as well as knowledge obtained from meta-analysis&#46;<span class="elsevierStyleSup">8</span> If&#44; in addition&#44; the variants to be analysed are located in regions of interest in the genes&#44; this translates&#44; for example&#44; in a change of amino acid &#40;non-synonymous variants&#41;&#44; or they affect the stability of the messenger processing&#59; or if the variant is located in regulating regions of the gene&#44; then that variant would probably be more useful&#46;<span class="elsevierStyleSup">11</span> Another strategy in the selection of candidate genes is the selection of tag variants&#44; i&#46;e&#46; variants on which there is prior information about&#44; information obtained by linkage studies and which at the same time can be linked to susceptibility alleles&#46;<span class="elsevierStyleSup">12</span></p><p class="elsevierStylePara">In such an active area as it is bioinformatics&#44; it is surprising that there is such a small number of tools aiding a key task as it is the selection of candidate genes&#46;<span class="elsevierStyleSup">13</span> There are&#44; however&#44; a number of on-line programmes&#58; <a href="http&#58;&#47;&#47;omicspace&#46;riken&#46;jp&#47;PosMed&#47;&#44;" class="elsevierStyleCrossRefs">http&#58;&#47;&#47;omicspace&#46;riken&#46;jp&#47;PosMed&#47;&#44;</a><a href="http&#58;&#47;&#47;www&#46;genesniffer&#46;org&#47;index&#47;index&#95;frameset&#46;htm" class="elsevierStyleCrossRefs">http&#58;&#47;&#47;www&#46;genesniffer&#46;org&#47;index&#47;index&#95;frameset&#46;htm</a>&#160; and <a href="http&#58;&#47;&#47;www&#46;genetics&#46;med&#46;ed&#46;ac&#46;uk&#47;suspects&#47;&#46;" class="elsevierStyleCrossRefs">http&#58;&#47;&#47;www&#46;genetics&#46;med&#46;ed&#46;ac&#46;uk&#47;suspects&#47;&#46;</a>&#160; These programmes are part of the information from platforms of high performance genetic analysis together with the information from expression studies allowing the appearance of the term convergence to region selection and candidate genes&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">QUANTIFIABLE PHENOTYPE AND EXPERIMENTAL DEMONSTRATION OF QUANTIFIABLE PHENOTYPE</span></p><p class="elsevierStylePara">Identifying and measuring the number of biologic parameters involved directly with the gene and its product or with the biologic pathway in which it is involved significantly increases the study information capacity&#46; It is more rigorous and&#44; in addition&#44; it is experimentally demonstrated that the variable itself associates with other variables in key regions of the gene or that it functionally affects either the gene or the protein&#46;<span class="elsevierStyleSup">6</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">DOES IT MAKE SENSE TO STUDY AND ANALYSE A RELATIVELY SMALL NUMBER OF POLYMORPHISMS&#63;</span></p><p class="elsevierStylePara">Analysing just one polymorphism can lead to spurious associations&#44; among other things&#44; because the variant may be at linkage disequilibrium with other variants&#44; thus forming a characteristic haplotype&#46; Sharma&#44; et al&#46;<span class="elsevierStyleSup">6</span> consider that for a candidate gene&#44; selection&#44; genotyping&#44; and frequency analysis of&#44; at least&#44; three common polymorphisms allows identifying variants at linkage disequilibrium and identifying synergies&#46; In a population-based case-control study where proximal SNPs have been genotyped and given that by definition the phase is unknown&#44; haplotypes may be inferred by using genetic software applications&#58; &#40;GDA&#58; http&#58;&#47;&#47;hydrodictyon&#46;eeb&#46;uconn&#46;edu&#47;people&#47;plewis&#47;software&#46;php and Arlequ&#237;n&#58; http&#58;&#47;&#47;lgb&#46;unige&#46;ch&#47;arlequin&#47;&#41;&#44; but it should not be determined in its totality&#44; neither should it be associated with a measurable phenotype in a give subject &#40;except those genotyped as homozygous for all the SNPs evaluated in a locus&#41;&#46; Nowadays&#44; information on haplotypes begins to be available in the Internet and it is therefore interesting to choose and validate the predictive or therapeutic usefulness of functional variants&#46;</p><p class="elsevierStylePara">Positive associations found in a given population using one or a few variants do not usually replicate in other populations&#46; Lack of replication is a fundamental argument against association studies amongst the most critical authors&#46; Apart from the problems derived from genotyping errors&#44; population mix&#44; election of candidate genes&#44; inadequate recruiting and characterization of cases and&#47;or controls&#44; and differences in environmental exposure&#44; there is lack of statistical power with absence of association &#40;table 4&#41; in most of the studies&#46; The solution is not simple&#44; and neither is it recruiting a larger number of cases and controls&#46;</p><p class="elsevierStylePara">A retrospective case-control genetic association study should therefore comply with a series of requirements succinctly presented below&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">LARGE SCALE GENOTYPING AND GENOME-WIDE OR GENOME-WHOLE ASSOCIATION STUDIES</span></p><p class="elsevierStylePara">The International HapMap Project &#40;http&#58;&#47;&#47;www&#46;hapmap&#46;org&#47;index&#46;html&#46;en&#41; is defined as a joint effort from many countries to identify and catalogue genetic similarities and differences in human beings at this level&#46;<span class="elsevierStyleSup">14</span> As mentioned above&#44; the methodology and interpretation of the results obtained differs from analysis of candidate genes in unrelated individuals&#46; High-performance genetic analysis platforms have changed the view of the association studies by making it possible to genotype multiple polymorphisms&#44; although necessarily enhancing the size of the sample&#46; Large-scale merging of genotyping technologies with the available information at the International HapMap Project has provided the possibility to perform genetic association studies using information termed as whole-genome association or wide-genome association &#40;WGA&#41;&#46; In these studies HapMap provides the information of the so-called &#191;tag SNPs&#191;&#44; defined as the minimum set of SNPs needed to detect a haplotype&#46; The project has gone through phases&#46; Trios were recruited in the first phase &#40;mother&#44; father&#44; and children&#41; from whom SNPs located at the distance of 5kb and with a frequency &#62; 5&#37; were identified&#46; A haplotype-like structure was then characterised to define the &#191;tags&#191;&#58; In a second phase&#44; identifying &#191;tags&#191; associated with a certain disease allows inferring the haplotype structure&#44; thus reducing the need to genotype all the variants and making it possible to locate the next candidate genes&#46; These types of studies&#44; although increasingly affordable&#44; today require significant human and financial resources&#44; but they are also an important step toward characterising clinically relevant variables&#46; The technology associated with genotyping is not however free from problems&#46;<span class="elsevierStyleSup">15</span> Even when an endeavour of such magnitude is carried out a few variants statistically associated with the disease survive the process of replication&#46;<span class="elsevierStyleSup">16</span> An added problem is the need of correction when multiple statistical comparisons are performed9&#44;10&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">CLINICAL USEFULNESS</span></p><p class="elsevierStylePara">The initial enthusiasm caused by the genetic association studies was based on how easily these allowed going a step further over the conventional epidemiological approach in the knowledge of disease causality and&#47;or risk factors associated with the disease &#40;figure 1&#41;&#46; For one or many candidate genes&#44; most health centres were able&#44; for example&#44; to carry out PCR amplifications and enzymatic digestion of a series of polymorphisms in genes of interest once their cases and controls had been recruited&#46; However&#44; this single information remained biased&#46; This relative ease allowed an exponential growth in the number of publications and&#44; concomitantly&#44; the appearance of a sector critical to its usefulness&#46; Some authors point out&#44; additionally&#44; that as the action or effect of certain variant within a gene must be interpreted within the context of a complex net including&#44; apart from interactions with other variants and the environment&#44; the complexity itself of the biological pathway where the gene is embedded&#44; the validity of an association strategy should be set out in the beginning&#46;<span class="elsevierStyleSup">7</span> In many studies carried out initially the main critical point was the lack of reproducibility in other series and populations&#46; However&#44; it is worth noting that the common denominator that in many cases justifies the lack of reproducibility does not depend so much on the population under analysis but&#44; as already remarked&#44; on the lack of statistical power&#44; which becomes the principal drawback&#46; Since the emerging technology allows increasing exponentially the number of variations to analyse&#44; good population recruitment becomes both the main requirement and a major problem&#46; In Spain&#44; the law of biomedical investigation 14&#47;2007 of 3 July&#44; regulates the type of genetic studies that can be performed&#44; the structure of informed consent necessary&#44; anonymisation process of samples and storage&#44; utilisation&#44; and transfer&#46; Consequently&#44; the following points are succinctly related to what has been mentioned above&#58; inadequate characterisation of the population to be studied&#44; lack of an adequate evaluation of the population&#44; inadequate recruitment of cases and&#47;or controls&#44; insufficient size of sample&#44; and lack of replication from analysed associations&#46; Certain scepticism arises that can&#44; however&#44; be counteracted with characterisation of adequate phenotypes&#44; analysis of intermediate phenotypes&#44; evaluation of measurable phenotypes&#44; haplotype characterisation&#44; and analysis of the population structure&#44; so that genetic association studies preserve their quality as one of the tools more powerful to a practical approach&#46;<span class="elsevierStyleSup">9</span></p><p class="elsevierStylePara"><a href="grande&#47;43718078&#95;t1&#95;p583&#46;jpg" class="elsevierStyleCrossRefs"><img src="43718078_t1_p583.jpg" alt="Variables that influence sample size assessment"></img></a></p><p class="elsevierStylePara">Table 1&#46; Variables that influence sample size assessment</p><p class="elsevierStylePara"><a href="grande&#47;43718078&#95;t2&#95;p584&#46;jpg" class="elsevierStyleCrossRefs"><img src="43718078_t2_p584.jpg" alt="Alternatives to face multiplicity"></img></a></p><p class="elsevierStylePara">Table 2&#46; Alternatives to face multiplicity</p><p class="elsevierStylePara"><a href="grande&#47;43718078&#95;t3&#95;p585&#46;jpg" class="elsevierStyleCrossRefs"><img src="43718078_t3_p585.jpg" alt="Type of statistical analysis employed"></img></a></p><p class="elsevierStylePara">Table 3&#46; Type of statistical analysis employed</p><p class="elsevierStylePara"><a href="grande&#47;43718078&#95;t4&#95;p586&#46;jpg" class="elsevierStyleCrossRefs"><img src="43718078_t4_p586.jpg" alt="Statistical power and study replicability"></img></a></p><p class="elsevierStylePara">Table 4&#46; Statistical power and study replicability</p><p class="elsevierStylePara"><a href="grande&#47;43718078&#95;f1&#95;p587&#46;jpg" class="elsevierStyleCrossRefs"><img src="43718078_f1_p587.jpg"></img></a></p><p class="elsevierStylePara">Figure 1&#46; </p>"
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Practical Guide to genetic association studies. Considerations on their clinical usefulness
Guía práctica a los estudios de asociación genética. Consideraciones sobre su utilidad clínica
F.. Rodríguez Esparragóna, José Carlos Rodríguez Pérezb, M.A.. García Belloa
a Unidad de Investigación, Hospital Universitario de Gran Canaria Dr. Negrín, Gran Canaria, Islas Canarias, España,
b Unidad de Investigación, Hospital Universitario de Gran Canaria Dr. Negrín, Universidad de Las Palmas de Gran Canaria, Gran Canaria, Islas Canarias, España,
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    "textoCompleto" => "<p class="elsevierStylePara"><span class="elsevierStyleBold">INTRODUCTION</span></p><p class="elsevierStylePara">The publication of a series of articles in the January issue of the journal JAMA titled &#191;How to use an article about genetic association&#191;<span class="elsevierStyleSup">1-3</span> serves as an excellent starting point to try a two-fold purpose&#58; to present&#44; similarly to what has been published&#44;a practical guide with the necessary requirements to face an article on genetic association&#44; and&#44; on the other hand&#44; to show the necessary tools to perform such a study&#46; To the present purpose&#44; we reduce the scope of action to those works on population based genetic association that are carried out by recruiting cases and controls considering that we will be evaluating candidate genes&#46; Methods and interpretation of results from family-based genetic studies are different and are not within the scope of this revision&#46; We insist in that our intention is only to point out a series of practical application guidelines and not to attempt any approach to genetic epidemiology&#46; We will therefore draw some considerations over the clinical relevance of these studies and analyse the current situation and its survival against genome-wide association studies&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">ARE THE PATIENTS APPROPRIATELY SELECTED&#63; PHENOTYPIC CHARACTERISATION</span></p><p class="elsevierStylePara">The adequate characterisation of a phenotype associated with certain disease is to be done in compliance with those clinical criteria over which there is a clearly established medical-scientific agreement&#46; Most scientific societies set these criteria and&#44; of course&#44; their corresponding updates&#44; as knowledge about disease progression and evolution is enhanced&#46; In real terms&#44; however&#44; it is not always possible to establish the right phenotype even when the guideline criteria are rigorously followed&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">IS SAMPLE SIZE THE RIGHT ONE&#63;</span></p><p class="elsevierStylePara">Assessing sample size &#40;table 1&#41; in a case-control study that includes genetic information is an object of constant study and remodeling&#46;<span class="elsevierStyleSup">4</span> A usual approach to assessing the sample size in a genetic association study does not differ from one in a usual clinical exposed&#47;not exposed-type study&#44; and it is based on previously establishing the magnitude of the difference to detect&#46; In our particular case&#44; it would mean to establish a priori the difference between the allelic or genotypic frequency in our populations&#46; In addition&#44; we have to know the frequency of alleles &#40;all those to be considered&#41; in the control population&#44; the value of type I error&#44; i&#46;e&#46; the error of rejecting the null hypothesis when the null hypothesis is true&#44; and type II error&#44; that is accepting the null hypothesis when the null hypothesis is false&#46; We usually play safe as not to make type I error in 95&#37; &#40;probability&#44; &#945; &#61; 0&#46;05&#41; and 5 to 20&#37; type II&#59; although&#44; it is usually set at 20&#37; &#40;probability&#44; &#946; &#61; 0&#46;2&#41;&#46; Thus a statistical power &#40;1 - &#946;&#41; of 80&#37; is ensured&#46; Other aspects should be considered too&#44; such as predictable error rate and type of errors to be expected in our genotyping procedure&#44; which should be compensated by a larger sample size so as not to reduce the statistical power&#46; Some &#191;on-line&#191; tools that help us in these calculations are&#44; among others&#58; http&#58;&#47;&#47;linkage&#46;rockefeller&#46;edu&#47;pawe&#47; y http&#58;&#47;&#47;hydra&#46;usc&#46;edu&#47;GxE&#47;&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">DISCUSSION OVER THE CASES</span></p><p class="elsevierStylePara">Ideally&#44; incident cases should be recruited&#46; Knowing in advance the allelic frequency of the variants to be studied and before proceeding to recruiting phase&#44; and being aware of the difficulty inherent in a given phenotype&#44; the number of subjects &#40;cases&#41; to be studied could be increased through various alternatives&#58; on the one hand&#44; by increasing the number while being less demanding when defining the phenotype&#44; as for example in &#171;renal disease&#187;&#44; thus increasing heterogeneity and reducing certainty to allele causality under evaluation&#59; on the other hand&#44; phenotype selection criteria could be more rigorous&#44; thus increasing homogeneity but necessarily reducing the number of cases recruited&#46; Alternatively&#44; phase duration for recruitment could be increased&#46; Choosing one alternative depends on various factors&#44; mainly on the allelic frequency of the variation&#40;s&#41; in the candidate gene&#40;s&#41; to be studied&#46; If an open criterion is chosen to select the cases&#44; it is to be expected that the candidate genes are present in a lower sub-group of our cases to study&#59; therefore&#44; due to the smaller effect size expected we will at least lose part of the statistical power that we intended to attain when defining our phenotype more broadly&#46; Hence&#44; when it comes to defining the cases we have to consider whether incrementing the cases available compensates for the loss in statistical power derived from a smaller difference in the frequencies expected&#46; If we postpone defining the phenotype until the moment when we have performed the analysis of our results&#44; we have alternatives&#46; Some authors&#44; such as Chen and Lee&#44; have created a simple quantitative method that allows us to clarify and systematize&#44; depending on the allelic frequencies and the existence of at least two possible types of &#171;cases&#187;&#44; when we can increase or not the size of our sample by linking both case types&#46;<span class="elsevierStyleSup">5</span> Nevertheless&#44; it is most scientifically appropriate to act in advance of these questions at the design phase of the study and not when we proceed to perform the statistical analysis&#44; since we might over-adjust the data thus obtaining spurious results that are difficult to replicate&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">DISCUSSION OVER THE CONTROLS</span></p><p class="elsevierStylePara">Arya Sharma and Xavier Jeunemaitre&#44;<span class="elsevierStyleSup">6</span> authors of renown in this area&#44; point at a common difficulty and error in the selection and control population recruitment&#46; The difficulty stems from the very nature of the control population&#46; While for most of the hospital researchers the inclusion of patients has not been a problem&#44; control recruiting has&#44; as it requires a population basis with specific resources&#46; Given that a control is potentially a case&#44; a usual bias is to include controls from&#44; for example&#44; blood banks or healthy workers in the area&#46; Selecting these candidates defined as &#171;hyper normal&#187; would theoretically result in a major difference in allelic frequencies between the affected and the control population&#44; but the advantage to this is indeed minimal and it might hide other phenotypes of positive selection toward survival&#46;<span class="elsevierStyleSup">7-9</span> Likewise&#44; selecting controls that are not diagnosed cases entails a reduction in the statistic power of our study&#46;<span class="elsevierStyleSup">10</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">ON STATISTICAL ANALYSIS AND STATISTICAL ASSOCIATION</span></p><p class="elsevierStylePara">We can set a phenotype selection that has to be studied characterising the phenotype as a dichotomous trait&#58; diabetics against non-diabetics&#44; hypertensive against normotensive&#44; or by trying to further delimit variability by reducing environmental uncertainty and gaining in phenotype influence through the evaluation of so-called intermediate phenotypes&#44; i&#46;e&#46; by evaluating one or many measurable characters that linked by plausible biological pathways our candidate gene&#40;s&#41; to the disease&#46; The most conventional statistical approach to either one alternative implies carrying out multivariate models&#46;</p><p class="elsevierStylePara">In studies with multiple comparisons we have to use corrections to avoid increasing type I error &#40;table 2&#41;&#46; Bonferroni procedure consists in dividing alpha by the number of comparisons to estimate&#58; if there are approximately 106 variants in the genome&#44; the threshold value of p corrected for all the comparisons would be p &#61; 0&#46;05&#47;106 &#61; 5 X 10-8&#46; If we intend to detect moderate differences this forces us to have a large sample size&#46; For this reason&#44; less conservative correction formulas are used&#44; such as the False Discovery Rate&#46; However&#44; when making numerous comparisons even using this procedure requires increasing the sample size too much&#46;</p><p class="elsevierStylePara">The statistical analysis used may give us a major statistical power &#40;table 3&#41;&#46; Thus&#44; if we know the genetic model &#40;additive-recessive-dominant&#41;&#44; we should use the Cochran-Armitage test&#46; However&#44; in general we do not know the genetic model of our candidate genes&#44; and although it gives us more power&#44; it is also true that it turns out to be less robust than the traditional Pearson&#191;s chi-square test&#44; which is the reason why in case of non-compliance with the cases we set up over the genetic model the results would become invalidated&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">ANALYSIS OF POPULATION MIX</span></p><p class="elsevierStylePara">The need&#44; in medicine&#44; to evaluate genetic heterogeneity in the population under study derives from the current evolution theory&#46; The studies show that although there is variation of frequency between alleles associated with the disease between dissimilar populations&#44; this is indeed quite small&#46;<span class="elsevierStyleSup">7</span> It might be the case that the association depended wholly on the exposure to certain environmental determinant whose frequency varied according to geographic localization and that frequency of these alleles by selection varied accordingly&#46;<span class="elsevierStyleSup">7</span> When population mixes are made that differ in allelic frequencies because of genetic or environmental reasons the association may turn out to be spurious&#46; Therefore the need for selection&#44; genotyping&#44; and neutral markers analysis &#40;null alleles&#44; unlinked SNPs&#44; insertions&#47;deletions&#41; through two different strategies termed &#191;genomic control&#191; and &#191;structured association&#191;&#58; http&#58;&#47;&#47;pritch&#46;bsd&#46;uchicago&#46;edu&#47;structure&#46;html and http&#58;&#47;&#47;wpicr&#46;wpic&#46;pitt&#46;edu&#47;WPICCompGen&#47;genomic&#95;control&#47;genomic&#95;control&#46;htm</p><p class="elsevierStylePara"><span class="elsevierStyleBold">SELECTION OF CANDIDATE GENES</span></p><p class="elsevierStylePara">Since in our approach we have decided to evaluate gene polymorphisms in candidates genes&#44; we are interested&#44; firstly&#44; in determining both the number and what genes we analyse&#46; The candidate genes under analysis are traditionally selected based on of the knowledge about the following&#58; gene product activity in the disease under study&#44; function of the protein coded by such gene&#44; information on studies in animal models&#44; knowledge presupposed from the phenotype associated with monogenic forms of the disease&#44; knowledge derived from gene linkage studies&#44; and data available a priori&#44; as well as knowledge obtained from meta-analysis&#46;<span class="elsevierStyleSup">8</span> If&#44; in addition&#44; the variants to be analysed are located in regions of interest in the genes&#44; this translates&#44; for example&#44; in a change of amino acid &#40;non-synonymous variants&#41;&#44; or they affect the stability of the messenger processing&#59; or if the variant is located in regulating regions of the gene&#44; then that variant would probably be more useful&#46;<span class="elsevierStyleSup">11</span> Another strategy in the selection of candidate genes is the selection of tag variants&#44; i&#46;e&#46; variants on which there is prior information about&#44; information obtained by linkage studies and which at the same time can be linked to susceptibility alleles&#46;<span class="elsevierStyleSup">12</span></p><p class="elsevierStylePara">In such an active area as it is bioinformatics&#44; it is surprising that there is such a small number of tools aiding a key task as it is the selection of candidate genes&#46;<span class="elsevierStyleSup">13</span> There are&#44; however&#44; a number of on-line programmes&#58; <a href="http&#58;&#47;&#47;omicspace&#46;riken&#46;jp&#47;PosMed&#47;&#44;" class="elsevierStyleCrossRefs">http&#58;&#47;&#47;omicspace&#46;riken&#46;jp&#47;PosMed&#47;&#44;</a><a href="http&#58;&#47;&#47;www&#46;genesniffer&#46;org&#47;index&#47;index&#95;frameset&#46;htm" class="elsevierStyleCrossRefs">http&#58;&#47;&#47;www&#46;genesniffer&#46;org&#47;index&#47;index&#95;frameset&#46;htm</a>&#160; and <a href="http&#58;&#47;&#47;www&#46;genetics&#46;med&#46;ed&#46;ac&#46;uk&#47;suspects&#47;&#46;" class="elsevierStyleCrossRefs">http&#58;&#47;&#47;www&#46;genetics&#46;med&#46;ed&#46;ac&#46;uk&#47;suspects&#47;&#46;</a>&#160; These programmes are part of the information from platforms of high performance genetic analysis together with the information from expression studies allowing the appearance of the term convergence to region selection and candidate genes&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">QUANTIFIABLE PHENOTYPE AND EXPERIMENTAL DEMONSTRATION OF QUANTIFIABLE PHENOTYPE</span></p><p class="elsevierStylePara">Identifying and measuring the number of biologic parameters involved directly with the gene and its product or with the biologic pathway in which it is involved significantly increases the study information capacity&#46; It is more rigorous and&#44; in addition&#44; it is experimentally demonstrated that the variable itself associates with other variables in key regions of the gene or that it functionally affects either the gene or the protein&#46;<span class="elsevierStyleSup">6</span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">DOES IT MAKE SENSE TO STUDY AND ANALYSE A RELATIVELY SMALL NUMBER OF POLYMORPHISMS&#63;</span></p><p class="elsevierStylePara">Analysing just one polymorphism can lead to spurious associations&#44; among other things&#44; because the variant may be at linkage disequilibrium with other variants&#44; thus forming a characteristic haplotype&#46; Sharma&#44; et al&#46;<span class="elsevierStyleSup">6</span> consider that for a candidate gene&#44; selection&#44; genotyping&#44; and frequency analysis of&#44; at least&#44; three common polymorphisms allows identifying variants at linkage disequilibrium and identifying synergies&#46; In a population-based case-control study where proximal SNPs have been genotyped and given that by definition the phase is unknown&#44; haplotypes may be inferred by using genetic software applications&#58; &#40;GDA&#58; http&#58;&#47;&#47;hydrodictyon&#46;eeb&#46;uconn&#46;edu&#47;people&#47;plewis&#47;software&#46;php and Arlequ&#237;n&#58; http&#58;&#47;&#47;lgb&#46;unige&#46;ch&#47;arlequin&#47;&#41;&#44; but it should not be determined in its totality&#44; neither should it be associated with a measurable phenotype in a give subject &#40;except those genotyped as homozygous for all the SNPs evaluated in a locus&#41;&#46; Nowadays&#44; information on haplotypes begins to be available in the Internet and it is therefore interesting to choose and validate the predictive or therapeutic usefulness of functional variants&#46;</p><p class="elsevierStylePara">Positive associations found in a given population using one or a few variants do not usually replicate in other populations&#46; Lack of replication is a fundamental argument against association studies amongst the most critical authors&#46; Apart from the problems derived from genotyping errors&#44; population mix&#44; election of candidate genes&#44; inadequate recruiting and characterization of cases and&#47;or controls&#44; and differences in environmental exposure&#44; there is lack of statistical power with absence of association &#40;table 4&#41; in most of the studies&#46; The solution is not simple&#44; and neither is it recruiting a larger number of cases and controls&#46;</p><p class="elsevierStylePara">A retrospective case-control genetic association study should therefore comply with a series of requirements succinctly presented below&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">LARGE SCALE GENOTYPING AND GENOME-WIDE OR GENOME-WHOLE ASSOCIATION STUDIES</span></p><p class="elsevierStylePara">The International HapMap Project &#40;http&#58;&#47;&#47;www&#46;hapmap&#46;org&#47;index&#46;html&#46;en&#41; is defined as a joint effort from many countries to identify and catalogue genetic similarities and differences in human beings at this level&#46;<span class="elsevierStyleSup">14</span> As mentioned above&#44; the methodology and interpretation of the results obtained differs from analysis of candidate genes in unrelated individuals&#46; High-performance genetic analysis platforms have changed the view of the association studies by making it possible to genotype multiple polymorphisms&#44; although necessarily enhancing the size of the sample&#46; Large-scale merging of genotyping technologies with the available information at the International HapMap Project has provided the possibility to perform genetic association studies using information termed as whole-genome association or wide-genome association &#40;WGA&#41;&#46; In these studies HapMap provides the information of the so-called &#191;tag SNPs&#191;&#44; defined as the minimum set of SNPs needed to detect a haplotype&#46; The project has gone through phases&#46; Trios were recruited in the first phase &#40;mother&#44; father&#44; and children&#41; from whom SNPs located at the distance of 5kb and with a frequency &#62; 5&#37; were identified&#46; A haplotype-like structure was then characterised to define the &#191;tags&#191;&#58; In a second phase&#44; identifying &#191;tags&#191; associated with a certain disease allows inferring the haplotype structure&#44; thus reducing the need to genotype all the variants and making it possible to locate the next candidate genes&#46; These types of studies&#44; although increasingly affordable&#44; today require significant human and financial resources&#44; but they are also an important step toward characterising clinically relevant variables&#46; The technology associated with genotyping is not however free from problems&#46;<span class="elsevierStyleSup">15</span> Even when an endeavour of such magnitude is carried out a few variants statistically associated with the disease survive the process of replication&#46;<span class="elsevierStyleSup">16</span> An added problem is the need of correction when multiple statistical comparisons are performed9&#44;10&#46;</p><p class="elsevierStylePara"><span class="elsevierStyleBold">CLINICAL USEFULNESS</span></p><p class="elsevierStylePara">The initial enthusiasm caused by the genetic association studies was based on how easily these allowed going a step further over the conventional epidemiological approach in the knowledge of disease causality and&#47;or risk factors associated with the disease &#40;figure 1&#41;&#46; For one or many candidate genes&#44; most health centres were able&#44; for example&#44; to carry out PCR amplifications and enzymatic digestion of a series of polymorphisms in genes of interest once their cases and controls had been recruited&#46; However&#44; this single information remained biased&#46; This relative ease allowed an exponential growth in the number of publications and&#44; concomitantly&#44; the appearance of a sector critical to its usefulness&#46; Some authors point out&#44; additionally&#44; that as the action or effect of certain variant within a gene must be interpreted within the context of a complex net including&#44; apart from interactions with other variants and the environment&#44; the complexity itself of the biological pathway where the gene is embedded&#44; the validity of an association strategy should be set out in the beginning&#46;<span class="elsevierStyleSup">7</span> In many studies carried out initially the main critical point was the lack of reproducibility in other series and populations&#46; However&#44; it is worth noting that the common denominator that in many cases justifies the lack of reproducibility does not depend so much on the population under analysis but&#44; as already remarked&#44; on the lack of statistical power&#44; which becomes the principal drawback&#46; Since the emerging technology allows increasing exponentially the number of variations to analyse&#44; good population recruitment becomes both the main requirement and a major problem&#46; In Spain&#44; the law of biomedical investigation 14&#47;2007 of 3 July&#44; regulates the type of genetic studies that can be performed&#44; the structure of informed consent necessary&#44; anonymisation process of samples and storage&#44; utilisation&#44; and transfer&#46; Consequently&#44; the following points are succinctly related to what has been mentioned above&#58; inadequate characterisation of the population to be studied&#44; lack of an adequate evaluation of the population&#44; inadequate recruitment of cases and&#47;or controls&#44; insufficient size of sample&#44; and lack of replication from analysed associations&#46; Certain scepticism arises that can&#44; however&#44; be counteracted with characterisation of adequate phenotypes&#44; analysis of intermediate phenotypes&#44; evaluation of measurable phenotypes&#44; haplotype characterisation&#44; and analysis of the population structure&#44; so that genetic association studies preserve their quality as one of the tools more powerful to a practical approach&#46;<span class="elsevierStyleSup">9</span></p><p class="elsevierStylePara"><a href="grande&#47;43718078&#95;t1&#95;p583&#46;jpg" class="elsevierStyleCrossRefs"><img src="43718078_t1_p583.jpg" alt="Variables that influence sample size assessment"></img></a></p><p class="elsevierStylePara">Table 1&#46; Variables that influence sample size assessment</p><p class="elsevierStylePara"><a href="grande&#47;43718078&#95;t2&#95;p584&#46;jpg" class="elsevierStyleCrossRefs"><img src="43718078_t2_p584.jpg" alt="Alternatives to face multiplicity"></img></a></p><p class="elsevierStylePara">Table 2&#46; Alternatives to face multiplicity</p><p class="elsevierStylePara"><a href="grande&#47;43718078&#95;t3&#95;p585&#46;jpg" class="elsevierStyleCrossRefs"><img src="43718078_t3_p585.jpg" alt="Type of statistical analysis employed"></img></a></p><p class="elsevierStylePara">Table 3&#46; Type of statistical analysis employed</p><p class="elsevierStylePara"><a href="grande&#47;43718078&#95;t4&#95;p586&#46;jpg" class="elsevierStyleCrossRefs"><img src="43718078_t4_p586.jpg" alt="Statistical power and study replicability"></img></a></p><p class="elsevierStylePara">Table 4&#46; Statistical power and study replicability</p><p class="elsevierStylePara"><a href="grande&#47;43718078&#95;f1&#95;p587&#46;jpg" class="elsevierStyleCrossRefs"><img src="43718078_f1_p587.jpg"></img></a></p><p class="elsevierStylePara">Figure 1&#46; </p>"
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Article information
ISSN: 20132514
Original language: English
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Year/Month Html Pdf Total
2024 November 7 14 21
2024 October 51 64 115
2024 September 52 74 126
2024 August 77 140 217
2024 July 53 43 96
2024 June 65 37 102
2024 May 81 43 124
2024 April 47 32 79
2024 March 51 35 86
2024 February 50 33 83
2024 January 61 36 97
2023 December 33 30 63
2023 November 67 32 99
2023 October 47 43 90
2023 September 33 28 61
2023 August 54 30 84
2023 July 72 36 108
2023 June 90 21 111
2023 May 70 34 104
2023 April 60 12 72
2023 March 93 27 120
2023 February 79 24 103
2023 January 62 11 73
2022 December 64 38 102
2022 November 80 32 112
2022 October 81 40 121
2022 September 63 30 93
2022 August 63 55 118
2022 July 61 48 109
2022 June 92 33 125
2022 May 70 47 117
2022 April 58 43 101
2022 March 63 65 128
2022 February 115 46 161
2022 January 87 52 139
2021 December 77 44 121
2021 November 86 60 146
2021 October 100 54 154
2021 September 85 57 142
2021 August 149 48 197
2021 July 118 56 174
2021 June 114 41 155
2021 May 92 51 143
2021 April 273 28 301
2021 March 166 28 194
2021 February 145 19 164
2021 January 106 24 130
2020 December 98 14 112
2020 November 109 28 137
2020 October 77 23 100
2020 September 96 26 122
2020 August 67 23 90
2020 July 95 21 116
2020 June 66 18 84
2020 May 96 25 121
2020 April 85 31 116
2020 March 88 21 109
2020 February 103 27 130
2020 January 109 25 134
2019 December 110 34 144
2019 November 104 30 134
2019 October 74 35 109
2019 September 83 28 111
2019 August 74 21 95
2019 July 67 33 100
2019 June 65 20 85
2019 May 107 43 150
2019 April 110 40 150
2019 March 70 33 103
2019 February 28 12 40
2019 January 48 20 68
2018 December 77 37 114
2018 November 143 10 153
2018 October 119 11 130
2018 September 95 14 109
2018 August 63 17 80
2018 July 55 12 67
2018 June 58 10 68
2018 May 53 17 70
2018 April 74 5 79
2018 March 78 7 85
2018 February 49 4 53
2018 January 53 5 58
2017 December 53 12 65
2017 November 38 5 43
2017 October 31 8 39
2017 September 36 10 46
2017 August 19 10 29
2017 July 24 11 35
2017 June 39 27 66
2017 May 45 2 47
2017 April 52 9 61
2017 March 55 19 74
2017 February 15 12 27
2017 January 18 7 25
2016 December 85 14 99
2016 November 61 5 66
2016 October 97 5 102
2016 September 130 2 132
2016 August 161 6 167
2016 July 128 0 128
2016 June 119 0 119
2016 May 125 0 125
2016 April 76 0 76
2016 March 73 0 73
2016 February 70 0 70
2016 January 85 0 85
2015 December 84 0 84
2015 November 81 0 81
2015 October 66 0 66
2015 September 72 0 72
2015 August 71 0 71
2015 July 55 0 55
2015 June 27 0 27
2015 May 47 0 47
2015 April 6 0 6
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¿Es usted profesional sanitario apto para prescribir o dispensar medicamentos?

Are you a health professional able to prescribe or dispense drugs?