Biomedical subjects

Daniel E Weeks

Publications and source records attributed to Daniel E Weeks.

At least 19 recordsLinked to original sources

PubMed2026

The Soifua Manuia reference panel with 2,570 Samoan haplotypes improves genotype imputation quality among Samoans.

Genotype imputation is fundamental to association studies, and yet even gold standard panels like TOPMed are limited in the populations for which they yield good imputation. Specifically, Pacific Islanders are poorly represented in extant panels. To address this, we used whole-genome sequencing from 1,285 Samoan individuals combined with 1000 Genomes Project (1KGP) individuals to construct an imputation reference panel that better represents Pacific Islander, specifically Samoan, genetic variation. Here we show that this panel yielded up to two times more well-imputed (r2 ≥ 0.80) variants than TOPMed-R3 and 1KGP and was enriched for moderate and high impact variants. There was improved imputation accuracy across the minor allele frequency (MAF) spectrum; accuracy (r2) was greater for population-specific variants (high fixation index, FST) and those from larger haplotypes (high LD score). However, the gain in accuracy over TOPMed-R3 was largest for small haplotypes, reflecting the Samoan panel's ability to capture variation not well tagged by other panels.

Haplotypes↗

PubMed2026

Variant harmonization critically determines polygenic score transferability for lipid traits in Samoan populations.

Dyslipidemia is a significant risk factor for cardiovascular disease (CVD), the leading cause of death in Samoa. Polygenic scores (PGSs) for lipid traits offer promise for improved CVD risk prediction; however, their performance in Pacific Islander populations-comprising only 0.002% of genome-wide association study (GWAS) participants as of 2024-remains unknown. We evaluated the transferability of multi-ancestry PGS for LDL cholesterol (LDL-C), HDL cholesterol (HDL-C), triglycerides (TGs), and total cholesterol (TC) in 4,342 Samoan adults across five cohorts spanning 1990-2010. PGSs from Graham et al. and Kanoni et al. multi-ancestry meta-analyses were harmonized with genome-wide imputed genotypes using a Samoan-specific reference panel, and performance was assessed via incremental R2 from linear mixed models with bootstrapped confidence intervals. HDL-C showed the highest performance (incremental R2 5.0%-15.0%), followed by TC (5.0%-10.7%), LDL-C (5.7%-8.6%), and TG (3.5%-7.0%). Critically, meaningful LDL-C performance was achieved only with the genome-wide PRS-CS score (99.6%-99.7% variant matching), while a curated pruning-and-thresholding score achieved ∼9% matching and near-zero performance. These findings establish systematic lipid PGS benchmarks in Samoans, demonstrating meaningful transferability when genome-wide variant coverage is ensured, and highlight variant harmonization as a critical precondition for PGS deployment in underrepresented populations.

Pacific Islanders↗

PubMed2026

Meta-analysis of over 8,000 individuals from Hawai'i and Samoa for genetic associations to cardiometabolic phenotypes.

Although genome-wide association studies (GWAS) now routinely reveal genetic associations and biological insights in millions of individuals, underrepresentation of global populations, such as those from Polynesia, continue to persist. These exclusions, often driven by logistical challenges and lack of data, prevent systematic identification of population-enriched associations, such as the association of the missense variant at the CREBRF locus to BMI and type 2 diabetes discovered commonly occurring in Polynesian populations due to its rarity in global populations. Armed with the recently updated TOPMed imputation panel that could benefit studies in diverse populations that previously had poorer imputation performance, we performed the first GWAS of Native Hawaiians and largest to date of Polynesian-ancestry populations (combined N up to 8,461) to identify population-enriched associations for 13 adiposity and cardiometabolic traits available across both cohorts: BMI, fasting glucose, fasting insulin, HDL, height, hip circumference, HOMA-IR, LDL, T2D, total cholesterol, triglycerides, waist circumference, and waist-hip ratio. We found 25 trait-loci associations that met genome-wide significance: 20 previously reported or known associations and 5 associations newly confirmed via meta-analysis. In particular, with improved statistical power, we were able to confirm the suspected association between the missense CREBRF variant with fasting glucose levels. The remaining 4 potentially novel loci-trait associations for BMI, LDL, and waist-hip ratio, however, were not replicated in multi-ethnic datasets from All-of-Us despite having reasonable power to replicate. The lack of Polynesian-enriched findings outside of the CREBRF locus informs the bounds of the effect sizes or frequency of any enriched variants, and suggests that further expansion of cohort sizes from this region of the world and improved imputation references specific to these populations are needed to identify more population-enriched associations.

Journal Article↗

PubMed2007

The elusive goal of pedigree weights.

Non-parametric linkage analysis methods generally involve calculating an allele-sharing statistic for each pedigree in a data set, then standardizing and summing the statistics over pedigrees. Pedigrees of different sizes can be weighted differently in the sum, though it is perhaps most common to weight all standardized pedigree statistics equally. Most other common weighting schemes are based on the number of affected individuals in the pedigree. It is also possible to derive optimal weights, which maximize power to detect linkage under particular trait models. We started by investigating three different analytical and simulation-based methods to calculate power and derive optimal weights. We found that simulation methods produce noticeably more accurate power calculations than the other methods. However, although the different calculation methods give different "optimal" weights, the power at those weights is very similar. That is, the analytical calculation methods are sufficient for finding good weights even though the simulation methods are most appropriate for calculating power. In comparing optimal weights for different trait models, we found that the weights vary quite a bit with the model, such that optimal weights for one model are not necessarily powerful at all for other models. Finally, we studied the power of a number of general weighting schemes, and of some new ones that incorporate information on how closely the affected individuals are related. We were able to find some schemes that performed well in the sense of giving reasonably powerful weights for most of the trait models and pedigree types we considered.

Chromosome Mapping↗

PubMed2006

Significant evidence of one or more susceptibility loci for endometriosis with near-Mendelian inheritance on chromosome 7p13-15.

BACKGROUND: Endometriosis is a common disease with a heritable component. The collaborative International Endogene Study consists of two data sets (Oxford and Australia) comprising 1176 families with multiple affected. The aim was to investigate whether the apparent concentration of cases in a proportion of families could be explained by one or more rare variants with (near-)Mendelian autosomal inheritance. METHODS AND RESULTS: Linkage analyses (aimed at finding chromosomal regions harbouring disease-predisposing genes) were conducted in families with three or more affected (Oxford: n = 52; Australia: n = 196). In the Oxford data set, a non-parametric linkage score (Kong & Cox (K&C) Log of ODds (LOD)) of 3.52 was observed on chromosome 7p (genome-wide significance P = 0.011). A parametric MOD score (equal to maximum LOD maximized over 357 possible inheritance models) of 3.89 was found at 65.72 cM (D7S510) for a dominant model with reduced penetrance. After including the Australian data set, the non-parametric K&C LOD of the combined data set was 1.46 at 57.3 cM; the parametric analysis found an MOD score of 3.30 at D7S484 (empirical significance: P = 0.035) for a recessive model with high penetrance. Critical recombinant analysis narrowed the probable region of linkage down to overlapping 6.4 Mb and 11 Mb intervals containing 48 and 96 genes, respectively. CONCLUSIONS: This is the first report to suggest that there may be one or more high-penetrance susceptibility loci for endometriosis with (near-)Mendelian inheritance.

Australia↗

PubMed2006

CFH, ELOVL4, PLEKHA1 and LOC387715 genes and susceptibility to age-related maculopathy: AREDS and CHS cohorts and meta-analyses.

Age-related maculopathy (ARM) is an important cause of visual impairment in the elderly population. It is of crucial importance to identify genetic factors and their interactions with environmental exposures for this disorder. This study was aimed at investigating the CFH, ELOVL4, PLEKHA1 and LOC387715 genes in independent cohorts collected using different ascertainment schemes. The study used a case-control design with subjects originally recruited through the Cardiovascular Health Study (CHS) and the Age-Related Eye Disease Study (AREDS). CFH was significantly associated with ARM in both cohorts (P</=0.00001). A meta-analysis confirmed that the risk allele in the heterozygous or homozygous state (OR, 2.4 and 6.2; 95% CI, 2.2-2.7 and 5.4-7.2, respectively) confers susceptibility. LOC387715 was also significantly associated with ARM in both cohorts (P</=0.00001) and a meta-analysis confirmed that the risk allele in the heterozygous and homozygous state (OR, 2.5 and 7.3; 95% CI, 2.2-2.9 and 5.7-9.4, respectively) confers susceptibility. Both CFH and LOC387715 showed an allele-dose effect on the ARM risk, individuals homozygous at either locus were at more than two-fold risk compared to those heterozygous. PLEKHA1, which is closely linked to LOC387715, was significantly associated with ARM status in the AREDS cohort, but not the CHS cohort and ELOVL4 was not significantly associated with ARM in either cohort. Joint action of CFH and LOC387715 was best described by independent multiplicative effect without significant interaction in both cohorts. Interaction of both genes with cigarette smoking was insignificant in both cohorts. This study provides additional support for the CFH and LOC387715 genes in ARM susceptibility via the evaluation of cohorts that had different ascertainment schemes regarding ARM status and through the meta-analyses.

Aged↗

PubMed2006

Treatment of uninformative families in mean allele sharing tests for linkage.

Using affected sibling pairs, the mean allele sharing statistic tests for linkage by testing if the mean proportion of alleles that are identical-by-descent (IBD) is equal to a half. The behavior of some versions of the mean allele sharing test statistic depends on whether or not families that are uninformative for their IBD status are included; the SIBPAL version provides less significant values when all families (informative and uninformative) are used than when only informative families are used. Here, we investigate this behavior both analytically and by simulation. Our investigation shows that the main issue is the choice of the variance estimator in the denominator of the statistic. The choice of the denominator is very important and is still not totally resolved. Our mathematical explanation supported by our simulation study might aid in the search for an optimum solution.

Alleles↗

PubMed2006

Ordered genotypes: an extended ITO method and a general formula for genetic covariance.

Traditionally, the stochastic ITO transition matrices provide a simple general method for obtaining the joint genotype distribution and genotypic correlations between any specified pair of noninbred relatives. The ITO method has been widely used in modern genetic analysis; however, since it was originally derived for unordered genotypes, it is not very useful in some new applications -- for example, when one is modeling genomic imprinting and must keep track of the parental origin of alleles. To address these new, emerging problems, here we extend the ITO method to handle ordered genotypes. Our extended method is applied to calculate the covariance in unilineal and bilineal relatives under genomic imprinting, and some generalized linear functions of the transition matrices are given. Since the ITO method is limited to biallelic loci and to unilineal and bilineal relatives, we derive a general formula for calculating the genetic covariance using ordered genotypes for any type of relative pair.

Alleles↗

PubMed2006

Comparison of methods incorporating quantitative covariates into affected sib pair linkage analysis.

For complex traits, it may be possible to increase the power to detect linkage if one takes advantage of covariate information. Several statistics have been proposed that incorporate quantitative covariate information into affected sib pair (ASP) linkage analysis. However, it is not clear how these statistics perform under different gene-environment (G x E) interactions. We compare representative statistics to each other on simulated data under three biologically-plausible G x E models. We also compared their performance with a model-free method and with quantitative trait locus (QTL) linkage approaches. The statistics considered here are: (1) mixture model; (2) general conditional-logistic model (LODPAL); (3) multinomial logistic regression models (MLRM); (4) extension of the maximum-likelihood-binomial approach (MLB); (5) ordered-subset analysis (OSA); and (6) logistic regression modeling (COVLINK). In all three G x E models, most of these six statistics perform better when using the covariate C1 associated with a G x E interaction effect than when using the environmental risk factor C2 or the random noise covariate C3. Compared with a model-free method without covariates (S(all)), the mixture model performs the best when using C1, with the high-to-low OSA method also performing quite well. Generally, MLB is the least sensitive to covariate choice. However, most of these statistics do not provide better power than S(all). Thus, while inclusion of the "correct" covariate can lead to increased power, careful selection of appropriate covariates is vital for success.

Analysis of Variance↗

PubMed2006

Gene-dropping vs. empirical variance estimation for allele-sharing linkage statistics.

In this study, we compare the statistical properties of a number of methods for estimating P-values for allele-sharing statistics in non-parametric linkage analysis. Some of the methods are based on the normality assumption, using different variance estimation methods, and others use simulation (gene-dropping) to find empirical distributions of the test statistics. For variance estimation methods, we consider the perfect variance approximation and two empirical variance estimates. The simulation-based methods are gene-dropping with and without conditioning on the observed founder alleles. We also consider the Kong and Cox linear and exponential models and a Monte Carlo method modified from a method for finding genome-wide significance levels. We discuss the analytical properties of these various P-value estimation methods and then present simulation results comparing them. Assuming that the sample sizes are large enough to justify a normality assumption for the linkage statistic, the best P-value estimation method depends to some extent on the (unknown) genetic model and on the types of pedigrees in the sample. If the sample sizes are not large enough to justify a normality assumption, then gene-dropping is the best choice. We discuss the differences between conditional and unconditional gene-dropping.

Alleles↗

PubMed2006

The Khatri Sikh Diabetes Study (SDS): study design, methodology, sample collection, and initial results.

Non-insulin-dependent diabetes mellitus, or type 2 diabetes (T2DM), has become a major public health problem in India. The high prevalence, relatively young age of onset, and strong familial aggregation of T2DM in some Indian communities remains to be explained. Many of the traditional risk factors established for European populations do not appear to be present in Asian Indians. Phase I of the Sikh Diabetes Study (SDS) was launched to build the population resources required to initiate a large-scale genetic epidemiological study of diabetes in an Asian Indian population. The SDS is focused on the Khatri Sikh population of North India. In all, 1,892 subjects were enrolled to participate in the family-based study; 1,623 of these subjects belong to 324 families, each of which has at least 2 siblings affected with T2DM. The sample included 1,288 individuals affected with T2DM (siblings, parents, or relatives) and 335 unaffected siblings, parents, or relatives. The remaining 269 subjects were unrelated nondiabetic control subjects, including unaffected spouses of probands or siblings. This primarily nonvegetarian, nonsmoking endogamous caste group has presented an unusual clinical picture of uneven distribution of adiposity and a high rate of T2DM with secondary complications. Such well-characterized population isolates may offer unique advantages in mapping genes for common complex diseases.

Adult↗

PubMed2005

Analysis of alcohol dependence phenotype in the COGA families using covariates to detect linkage.

Linkage analysis methods that incorporate etiological heterogeneity of complex diseases are likely to demonstrate greater power than traditional linkage analysis methods. Several such methods use covariates to discriminate between linked and unlinked pedigrees with respect to a certain disease locus. Here we apply several such methods including two mixture models, ordered subset analysis, and a conditional logistic model to genome scan data on the DSM-IV alcohol dependence phenotype on the Collaborative Studies on Genetics of Alcoholism families, and compare the results to traditional nonparametric linkage analysis. In general, there was little agreement among the various covariate-based linkage statistics. Linkage signals with empirical p-values less than 0.001 were detected on chromosomes 3, 4, 7, 10, and 12, with the highest peak occurring at the GABRB1 gene using the ecb21 covariate.

Alcoholism↗

PubMed2005

A comparison between microsatellite and single-nucleotide polymorphism markers with respect to two measures of information content.

Using the Genetic Analysis Workshop 14 (GAW14) simulated dataset, we compare microsatellite and single-nucleotide polymorphism (SNP) markers in terms of two measures of information content, the traditional entropy-based information content measure, and a new "relative information" measure. Both attempt to measure the amount of information contained in the markers about the identity-by-descent (IBD) sharing among relatives. The performance of the two information measures are compared based on their variability and ability to predict change in the LOD score (Delta LOD) as map density increases for SNP markers. Although in a linked region, LOD scores are correlated with measures of information, we observe that none of the measures predict the LOD score itself very well. In an unlinked region, the LOD score is not related to either measures of information. The information content of microsatellite markers with 7.5-cM spacing is slightly higher than that of SNP markers with 3-cM spacing. At these map densities, microsatellites are found to be uniformly more informative than SNPs irrespective of their level of heterozygosity. For SNPs, we found that as the level of heterozygosity increases, the information content increases. As reported in all other previous studies, we also found that high-density SNPs have higher information content compared to low-density microsatellites. Performance of both the two information measures considered here are similar, but the relative information measure predicts Delta LOD as marker density increases better than the traditional entropy-based information measure.

Genetic Markers↗

PubMed2005

Susceptibility genes for age-related maculopathy on chromosome 10q26.

On the basis of genomewide linkage studies of families affected with age-related maculopathy (ARM), we previously identified a significant linkage peak on 10q26, which has been independently replicated by several groups. We performed a focused SNP genotyping study of our families and an additional control cohort. We identified a strong association signal overlying three genes, PLEKHA1, LOC387715, and PRSS11. All nonsynonymous SNPs in this critical region were genotyped, yielding a highly significant association (P < .00001) between PLEKHA1/LOC387715 and ARM. Although it is difficult to determine statistically which of these two genes is most important, SNPs in PLEKHA1 are more likely to account for the linkage signal in this region than are SNPs in LOC387715; thus, this gene and its alleles are implicated as an important risk factor for ARM. We also found weaker evidence supporting the possible involvement of the GRK5/RGS10 locus in ARM. These associations appear to be independent of the association of ARM with the Y402H allele of complement factor H, which has previously been reported as a major susceptibility factor for ARM. The combination of our analyses strongly implicates PLEKHA1/LOC387715 as primarily responsible for the evidence of linkage of ARM to the 10q26 locus and as a major contributor to ARM susceptibility. The association of either a single or a double copy of the high-risk allele within the PLEKHA1/LOC387715 locus accounts for an odds ratio of 5.0 (95% confidence interval 3.2-7.9) for ARM and a population attributable risk as high as 57%.

Case-Control Studies↗

PubMed2005

Genomewide linkage study in 1,176 affected sister pair families identifies a significant susceptibility locus for endometriosis on chromosome 10q26.

Endometriosis is a common gynecological disease that affects up to 10% of women in their reproductive years. It causes pelvic pain, severe dysmenorrhea, and subfertility. The disease is defined as the presence of tissue resembling endometrium in sites outside the uterus. Its cause remains uncertain despite >50 years of hypothesis-driven research, and thus the therapeutic options are limited. Disease predisposition is inherited as a complex genetic trait, which provides an alternative route to understanding the disease. We seek to identify susceptibility loci, using a positional-cloning approach that starts with linkage analysis to identify genomic regions likely to harbor these genes. We conducted a linkage study of 1,176 families (931 from an Australian group and 245 from a U.K. group), each with at least two members--mainly affected sister pairs--with surgically diagnosed disease. We have identified a region of significant linkage on chromosome 10q26 (maximum LOD score [MLS] of 3.09; genomewide P = .047) and another region of suggestive linkage on chromosome 20p13 (MLS = 2.09). Minor peaks (with MLS > 1.0) were found on chromosomes 2, 6, 7, 8, 12, 14, 15, and 17. This is the first report of linkage to a major locus for endometriosis. The findings will facilitate discovery of novel positional genetic variants that influence the risk of developing this debilitating disease. Greater understanding of the aberrant cellular and molecular mechanisms involved in the etiology and pathophysiology of endometriosis should lead to better diagnostic methods and targeted treatments.

Australia↗

PubMed2005

Meta-analysis of genome scans of age-related macular degeneration.

A genetic contribution to the development of age-related macular degeneration (AMD) is well established. Several genome-wide linkage studies have identified a number of putative susceptibility loci for AMD but only a few of these regions have been replicated in independent studies. Here, we perform a meta-analysis of six AMD genome screens using the genome-scan meta-analysis method, which allows linkage results from several studies to be combined, providing greater power to identify regions that show only weak evidence for linkage in individual studies. Results from non-parametric analysis for a broad AMD clinical phenotype (including two studies with quantitative traits) were extracted. For each study, 120 genomic bins of approximately 30 cM were defined and ranked according to maximum evidence for linkage within each bin. Bin ranks were weighted according to study size and summed across all studies; the summed rank (SR) for each bin was assessed empirically for significance using permutation methods. A high SR indicates a region with consistent evidence for linkage across studies. The strongest evidence for an AMD susceptibility locus was found on chromosome 10q26 where genome-wide significant linkage was observed (P=0.00025). Several other regions met the empirical significance criteria for bins likely to contain linked loci including adjacent pairs of bins on chromosomes 1q, 2p, 3p and 16. Several of the regions identified here showed only weak evidence for linkage in the individual studies. These results will help prioritize regions for future positional and functional candidate gene studies in AMD.

Aging↗

PubMed2005

Candidate gene analysis suggests a role for fatty acid biosynthesis and regulation of the complement system in the etiology of age-related maculopathy.

Age-related maculopathy (ARM) is a leading cause of visual impairment in elderly Americans and is a complex genetic disorder. Hypothesized pathways for the etiology of ARM include cholesterol and lipoprotein metabolism and transport, extracellular matrix integrity, oxidative stress and inflammatory/immunologic processes. This study investigates 21 polymorphisms within 15 candidate genes whose products function within these pathways by performing family and case-control genetic association studies using clearly affected familial cases (n=338 families, 796 individuals), clearly affected, unrelated sporadic cases (n=196) and clearly unaffected, unrelated controls (n=120). Two genes demonstrated significant association with ARM status. A Met299Val variant in the elongation of very long chain fatty acids-like 4 (ELOVL4) gene was significantly associated with ARM in the case-control allele (P=0.001), case-control genotype (P=0.001) and case-control family (P<0.0001) tests. A Tyr402His variant in exon 9 in the complement factor H (CFH) gene was also significantly associated with ARM in the case-control allele (P<0.0001), case-control genotype (P<0.0001) and case-control family (P<0.0001) tests. All of these results remain significant after adjusting for false discovery rates to control for the impact of multiple testing. In addition, the CFH variant appears to play a role in exudative and atrophic disease, whereas the ELOVL4 variant may play a greater role in exudative disease in our population. These results support a potential role for multiple pathways in the etiology of ARM, including pathways involved with fatty acid biosynthesis and the complement system.

Aging↗

PubMed2005

Candidate-gene screening and association analysis at the autism-susceptibility locus on chromosome 16p: evidence of association at GRIN2A and ABAT.

Autism is a highly heritable neurodevelopmental disorder whose underlying genetic causes have yet to be identified. To date, there have been eight genome screens for autism, two of which identified a putative susceptibility locus on chromosome 16p. In the present study, 10 positional candidate genes that map to 16p11-13 were examined for coding variants: A2BP1, ABAT, BFAR, CREBBP, EMP2, GRIN2A, MRTF-B, SSTR5, TBX6, and UBN1. Screening of all coding and regulatory regions by denaturing high-performance liquid chromatography identified seven nonsynonymous changes. Five of these mutations were found to cosegregate with autism, but the mutations are not predicted to have deleterious effects on protein structure and are unlikely to represent significant etiological variants. Selected variants from candidate genes were genotyped in the entire International Molecular Genetics Study of Autism Consortium collection of 239 multiplex families and were tested for association with autism by use of the pedigree disequilibrium test. Additionally, genotype frequencies were compared between 239 unrelated affected individuals and 192 controls. Patterns of linkage disequilibrium were investigated, and the transmission of haplotypes across candidate genes was tested for association. Evidence of single-marker association was found for variants in ABAT, CREBBP, and GRIN2A. Within these genes, 12 single-nucleotide polymorphisms (SNPs) were subsequently genotyped in 91 autism trios (one affected individual and two unaffected parents), and the association was replicated within GRIN2A (Fisher's exact test, P<.0001). Logistic regression analysis of SNP data across GRIN2A and ABAT showed a trend toward haplotypic differences between cases and controls.

4-Aminobutyrate Transaminase↗