Familial Hypercholesterolemia Variant and Cardiovascular Risk in Individuals With Elevated Cholesterol.

Importance: Familial hypercholesterolemia (FH) is a genetic disorder that often results in severely high low-density lipoprotein cholesterol (LDL-C) and high risk of premature coronary heart disease (CHD). However, the impact of FH variants on CHD risk among individuals with moderately elevated LDL-C is not well quantified. Objective: To assess CHD risk associated with FH variants among individuals with moderately (130-189 mg/dL) and severely (≥190 mg/dL) elevated LDL-C and to quantify excess CHD deaths attributable to FH variants in US adults. Design, Setting, and Participants: A total of 21 426 individuals without preexisting CHD from 6 US cohort studies (Atherosclerosis Risk in Communities study, Coronary Artery Risk Development in Young Adults study, Cardiovascular Health Study, Framingham Heart Study Offspring cohort, Jackson Heart Study, and Multi-Ethnic Study of Atherosclerosis) were included, 63 of whom had an FH variant. Data were collected from 1971 to 2018, and the median (IQR) follow-up was 18 (13-28) years. Data were analyzed from March to May 2023. Exposures: LDL-C, cumulative past LDL-C, FH variant status. Main Outcomes and Measures: Cox proportional hazards models estimated associations between FH variants and incident CHD. The Cardiovascular Disease Policy Model projected excess CHD deaths associated with FH variants in US adults. Results: Of the 21 426 individuals without preexisting CHD (mean [SD] age 52.1 [15.5] years; 12 041 [56.2%] female), an FH variant was found in 22 individuals with moderately elevated LDL-C (0.3%) and in 33 individuals with severely elevated LDL-C (2.5%). The adjusted hazard ratios for incident CHD comparing those with and without FH variants were 2.9 (95% CI, 1.4-6.0) and 2.6 (95% CI, 1.4-4.9) among individuals with moderately and severely elevated LDL-C, respectively. The association between FH variants and CHD was slightly attenuated when further adjusting for baseline LDL-C level, whereas the association was no longer statistically significant after adjusting for cumulative past LDL-C exposure. Among US adults 20 years and older with no history of CHD and LDL-C 130 mg/dL or higher, more than 417 000 carry an FH variant and were projected to experience more than 12 000 excess CHD deaths in those with moderately elevated LDL-C and 15 000 in those with severely elevated LDL-C compared with individuals without an FH variant. Conclusions and Relevance: In this pooled cohort study, the presence of FH variants was associated with a 2-fold higher CHD risk, even when LDL-C was only moderately elevated. The increased CHD risk appeared to be largely explained by the higher cumulative LDL-C exposure in individuals with an FH variant compared to those without. Further research is needed to assess the value of adding genetic testing to traditional phenotypic FH screening.

Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits.

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.

The Framingham Heart Study 100K SNP genome-wide association study resource: overview of 17 phenotype working group reports.

BACKGROUND: The Framingham Heart Study (FHS), founded in 1948 to examine the epidemiology of cardiovascular disease, is among the most comprehensively characterized multi-generational studies in the world. Many collected phenotypes have substantial genetic contributors; yet most genetic determinants remain to be identified. Using single nucleotide polymorphisms (SNPs) from a 100K genome-wide scan, we examine the associations of common polymorphisms with phenotypic variation in this community-based cohort and provide a full-disclosure, web-based resource of results for future replication studies. METHODS: Adult participants (n = 1345) of the largest 310 pedigrees in the FHS, many biologically related, were genotyped with the 100K Affymetrix GeneChip. These genotypes were used to assess their contribution to 987 phenotypes collected in FHS over 56 years of follow up, including: cardiovascular risk factors and biomarkers; subclinical and clinical cardiovascular disease; cancer and longevity traits; and traits in pulmonary, sleep, neurology, renal, and bone domains. We conducted genome-wide variance components linkage and population-based and family-based association tests. RESULTS: The participants were white of European descent and from the FHS Original and Offspring Cohorts (examination 1 Offspring mean age 32 +/- 9 years, 54% women). This overview summarizes the methods, selected findings and limitations of the results presented in the accompanying series of 17 manuscripts. The presented association results are based on 70,897 autosomal SNPs meeting the following criteria: minor allele frequency > or + 10%, genotype call rate > or = 80%, Hardy-Weinberg equilibrium p-value > or = 0.001, and satisfying Mendelian consistency. Linkage analyses are based on 11,200 SNPs and short-tandem repeats. Results of phenotype-genotype linkages and associations for all autosomal SNPs are posted on the NCBI dbGaP website at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007 webcite. CONCLUSION: We have created a full-disclosure resource of results, posted on the dbGaP website, from a genome-wide association study in the FHS. Because we used three analytical approaches to examine the association and linkage of 987 phenotypes with thousands of SNPs, our results must be considered hypothesis-generating and need to be replicated. Results from the FHS 100K project with NCBI web posting provides a resource for investigators to identify high priority findings for replication.

Genomewide linkage analysis of weight change in the Framingham Heart Study.

BACKGROUND: Weight gain adversely affects blood pressure, lipids, and glycemia. The genetic contribution to weight change is unknown. METHODS: Variance components linkage analysis using microsatellites was performed on 336 families from the Framingham Heart Study offspring cohort, using a 10-cM genome-wide linkage analysis. We evaluated linkage to two traits: short-term (8-yr) weight change and long-term (up to 24-yr) weight change. Models were adjusted for age, age squared, baseline weight, smoking status, and menopausal status. RESULTS: Mean short-term weight change ranged from 1.4-3.8 kg, and mean long-term weight change was 7.7 kg. The heritability of long-term weight change was 0.24; weight change was minimally heritable among younger individuals and over shorter follow-up intervals. We found significant evidence for linkage for long-term weight change, with a peak LOD score of 3.10 on chromosome 20 at 63.7 cM (nearest marker, D20S481). We also found suggestive evidence for linkage on chromosome 1 at 239.7 cM (LOD score, 2.28; nearest marker, D1S1644). CONCLUSION: Long-term weight change is heritable, and evidence for linkage exists on chromosomes 1 and 20. Potential candidate genes include MC3R, ASIP, AGT, and HSD11B1. Additional research is necessary to uncover the genetic underpinnings of weight change that might contribute to associated adverse metabolic profiles.