Lai, Dongbing

Objective The aim of this study was to search for genes/variants that modify the effect of LRRK2 mutations in terms of penetrance and age‐at‐onset of Parkinson's disease. Methods We performed the first genomewide association study of penetrance and age‐at‐onset of Parkinson's disease in LRRK2 mutation carriers (776 cases and 1,103 non‐cases at their last evaluation). Cox proportional hazard models and linear mixed models were used to identify modifiers of penetrance and age‐at‐onset of LRRK2 mutations, respectively. We also investigated whether a polygenic risk score derived from a published genomewide association study of Parkinson's disease was able to explain variability in penetrance and age‐at‐onset in LRRK2 mutation carriers. Results A variant located in the intronic region of CORO1C on chromosome 12 (rs77395454; p value = 2.5E‐08, beta = 1.27, SE = 0.23, risk allele: C) met genomewide significance for the penetrance model. Co‐immunoprecipitation analyses of LRRK2 and CORO1C supported an interaction between these 2 proteins. A region on chromosome 3, within a previously reported linkage peak for Parkinson's disease susceptibility, showed suggestive associations in both models (penetrance top variant: p value = 1.1E‐07; age‐at‐onset top variant: p value = 9.3E‐07). A polygenic risk score derived from publicly available Parkinson's disease summary statistics was a significant predictor of penetrance, but not of age‐at‐onset. Interpretation This study suggests that variants within or near CORO1C may modify the penetrance of LRRK2 mutations. In addition, common Parkinson's disease associated variants collectively increase the penetrance of LRRK2 mutations. ANN NEUROL 2021;90:82–94

Abstract Eating disorders and substance use disorders frequently co‐occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [ r g ], twin‐based = 0.23‐0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome‐wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance‐use‐related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism‐based genetic correlations between eating disorder‐ and substance‐use‐related phenotypes. Significant positive genetic associations emerged between AUD and AN ( r g = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN ( r g = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating ( r g = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating ( r gs = −0.19 to −0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co‐varying for major depressive disorder loci. The patterns of association between eating disorder‐ and substance‐use‐related phenotypes highlights the potentially complex and substance‐specific relationships among these behaviors.

Background Intracranial aneurysms ( IAs ), abdominal aortic aneurysms ( AAAs ), and thoracic aortic aneurysms ( TAAs ) all have a familial predisposition. Given that aneurysm types are known to co‐occur, we hypothesized that there may be shared genetic risk factors for IAs , AAAs, and TAAs . Methods and Results We performed a mega‐analysis of 1000 Genomes Project‐imputed genome‐wide association study ( GWAS ) data of 4 previously published aneurysm cohorts: 2 IA cohorts (in total 1516 cases, 4305 controls), 1 AAA cohort (818 cases, 3004 controls), and 1 TAA cohort (760 cases, 2212 controls), and observed associations of 4 known IA , AAA , and/or TAA risk loci (9p21, 18q11, 15q21, and 2q33) with consistent effect directions in all 4 cohorts. We calculated polygenic scores based on IA ‐, AAA ‐, and TAA ‐associated SNP s and tested these scores for association to case‐control status in the other aneurysm cohorts; this revealed no shared polygenic effects. Similarly, linkage disequilibrium–score regression analyses did not show significant correlations between any pair of aneurysm subtypes. Last, we evaluated the evidence for 14 previously published aneurysm risk single‐nucleotide polymorphisms through collaboration in extended aneurysm cohorts, with a total of 6548 cases and 16 843 controls ( IA ) and 4391 cases and 37 904 controls ( AAA ), and found nominally significant associations for IA risk locus 18q11 near RBBP 8 to AAA (odds ratio [ OR ]=1.11; P =4.1×10 −5 ) and for TAA risk locus 15q21 near FBN 1 to AAA ( OR =1.07; P =1.1×10 −3 ). Conclusions Although there was no evidence for polygenic overlap between IAs , AAAs , and TAAs , we found nominally significant effects of two established risk loci for IAs and TAAs in AAAs . These two loci will require further replication.

Background and Purpose— The purpose of this study was to replicate the previous association of single nucleotide polymorphisms (SNPs) with risk of intracranial aneurysm (IA) and to examine the relationship of smoking with these variants and the risk of IA. Methods— White probands with an IA from families with multiple affected members were identified by 26 clinical centers located throughout North America, New Zealand, and Australia. White control subjects free of stroke and IA were selected by random digit dialing from the Greater Cincinnati population. SNPs previously associated with IA on chromosomes 2, 8, and 9 were genotyped using a TaqMan assay or were included in the Affymetrix 6.0 array that was part of a genomewide association study of 406 IA cases and 392 control subjects. Logistic regression modeling tested whether the association of replicated SNPs with IA was modulated by smoking. Results— The strongest evidence of association with IA was found with the 8q SNP rs10958409 (genotypic P =9.2×10 −5 ; allelic P =1.3×10 −5 ; OR=1.86, 95% CI: 1.40 to 2.47). We also replicated the association with both SNPs on chromosome 9p, rs1333040 and rs10757278, but were not able to replicate the previously reported association of the 2 SNPs on chromosome 2q. Statistical testing showed a multiplicative relationship between the risk alleles and smoking with regard to the risk of IA. Conclusion— Our data provide complementary evidence that the variants on chromosomes 8q and 9p are associated with IA and that the risk of IA in patients with these variants is greatly increased with cigarette smoking.

Background and Purpose— Risk for both intracranial aneurysms (IAs) and aortic aneurysms (AAs) is thought to be heritable with mounting evidence for genetic predisposition. The concept of shared risk for these conditions is challenged by differences in age of diagnosis and demographic characteristics. We performed a genomewide linkage analysis in multiplex families with both IA and AA from the Familial Intracranial Aneurysm study. Methods— Available medical records of subjects who reported IA or abdominal/thoracic AA were reviewed with adjudication as definite/probable, possible, or not a case. To identify genes contributing to the susceptibility for IA and AA, genomewide linkage analysis was performed in the 26 multiplex IA families who had members who also had thoracic or abdominal AA. Individuals (n=91) were defined as affected if they had an IA (definite/probable) or an aortic or thoracic AA (definite/probable). Results— Maximum logarithm of odds (LOD) scores were found on chromosomes 11 (144 cM; LOD=3.0) and 6 (33 cM; LOD=2.3). In both chromosomal regions, analyses of these same 26 families considering only IA as the disease phenotype produced LOD scores of 1.8 and 1.6, respectively. Conclusions— Our linkage analysis in these 26 families using the broadest disease phenotype, including IA, abdominal AA, and thoracic AA, supports the concept of shared genetic risk. The chromosome 11 locus appears to confirm earlier independent associations in IA and AA. The chromosome 6 finding is novel. Both warrant further investigation.

Background and Purpose— Evidence supports a substantial genetic contribution to the risk of intracranial aneurysm (IA). The purpose of this study was to identify chromosomal regions likely to harbor genes that contribute to the risk of IA. Methods— Multiplex families having at least 2 individuals with “definite” or “probable” IA were ascertained through an international consortium. First-degree relatives of individuals with IA who were at increased risk of an IA because of a history of hypertension or present smoking were offered cerebral magnetic resonance angiography. A genome screen was completed using the Illumina 6K SNP system, and the resulting data from 192 families, containing 1155 genotyped individuals, were analyzed. Narrow and broad disease definitions were used when testing for linkage using multipoint model-independent methods. Ordered subset analysis was performed to test for a gene×smoking (pack-years) interaction. Results— The greatest evidence of linkage was found on chromosomes 4 (LOD=2.5; 156 cM), 7 (LOD=1.7; 183 cM), 8 (LOD=1.9; 70 cM), and 12 (LOD=1.6; 102 cM) using the broad disease definition. Using the average pack-years for the affected individuals in each family, the genes on chromosomes 4 (LOD=3.5; P =0.03), 7 (LOD=4.1; P =0.01) and 12 (LOD=3.6; P =0.02) all appear to be modulated by the degree of smoking in the affected members of the family. On chromosome 8, inclusion of smoking as a covariate did not significantly strengthen the linkage evidence, suggesting no interaction between the loci in this region and smoking. Conclusions— We have detected possible evidence of linkage to 4 chromosomal regions. There is potential evidence for a gene×smoking interaction with 3 of the loci.