👤 Anthony J Swerdlow

Alzheimer's disease (AD) involves proteostasis dysregulation causing protein misfolding, but whether these structural changes manifest as plasma conformational biomarkers remains unclear. We profiled plasma protein structures from 520 participants including individuals with AD, individuals with mild cognitive impairment (MCI) and healthy controls. Using mass spectrometry and machine learning, we systematically characterized the structural proteome changes associated with ApoE variations and neuropsychiatric symptoms to identify AD-specific signatures. We developed a diagnostic panel using peptides from C1QA, CLUS and ApoB representing AD-associated structural changes. This three-marker panel achieved 83.44% accuracy in three-way classification (healthy versus MCI versus AD). Binary classification yielded area under the receiver operating characteristic curves of 0.9343 for healthy versus MCI and 0.9325 for MCI versus AD. Longitudinal samples were classified with 86.0% accuracy. This multi-marker panel based on plasma protein structural alterations represents a promising diagnostic approach that may enhance early AD detection and provide insights for clinical trials, improving therapeutic outcomes. Show less

Alzheimer's disease (AD) pathology is complex and involves mitochondrial dysfunction. There are emerging therapies targeting mitochondrial function in clinical trials for AD. This highlights the need for biomarkers that measure mitochondrial function. We determined the utility of a novel blood-based mitochondrial biomarker, the mitochondrial functional index (MFI), in the context of AD in a pilot study. In vitro and in vivo models of AD had a reduced MFI. MFI was lower in human AD subjects and APOE 𝜀4 carriers. Receiver operating characteristic analysis showed MFI had a higher area under the curve than other plasma biomarkers. The MFI biomarker correlated with the Mini-Mental State Examination (MMSE) and the Clinical Dementia Rating (CDR) scale. This study highlights the potential utility of MFI as a functional blood-based mitochondrial biomarker to interrogate energy metabolism. Ongoing studies are examining the relationship of MFI with brain energy metabolism outcomes. The MFI biomarker is reduced in cell and animal models of AD. The MFI biomarker is reduced in human AD subjects and APOE ε4 carriers. The MFI biomarker can discriminate between subjects with normal cognition and AD with better performance than other plasma biomarkers. The MFI biomarker correlates with cognitive scores. Show less

The HERMES (HEart failure Molecular Epidemiology for Therapeutic targetS) consortium aims to identify the genomic and molecular basis of heart failure. The consortium currently includes 51 studies from 11 countries, including 68 157 heart failure cases and 949 888 controls, with data on heart failure events and prognosis. All studies collected biological samples and performed genome-wide genotyping of common genetic variants. The enrolment of subjects into participating studies ranged from 1948 to the present day, and the median follow-up following heart failure diagnosis ranged from 2 to 116 months. Forty-nine of 51 individual studies enrolled participants of both sexes; in these studies, participants with heart failure were predominantly male (34-90%). The mean age at diagnosis or ascertainment across all studies ranged from 54 to 84 years. Based on the aggregate sample, we estimated 80% power to genetic variant associations with risk of heart failure with an odds ratio of ≥1.10 for common variants (allele frequency ≥ 0.05) and ≥1.20 for low-frequency variants (allele frequency 0.01-0.05) at P < 5 × 10 HERMES is a global collaboration aiming to (i) identify the genetic determinants of heart failure; (ii) generate insights into the causal pathways leading to heart failure and enable genetic approaches to target prioritization; and (iii) develop genomic tools for disease stratification and risk prediction. Show less

Risk factors for abdominal aortic aneurysm (AAA) are largely unknown, which has hampered the development of nonsurgical treatments to alter the natural history of disease. To investigate the association between lipid-associated single-nucleotide polymorphisms (SNPs) and AAA risk. Genetic risk scores, composed of lipid trait-associated SNPs, were constructed and tested for their association with AAA using conventional (inverse-variance weighted) mendelian randomization (MR) and data from international AAA genome-wide association studies. Sensitivity analyses to account for potential genetic pleiotropy included MR-Egger and weighted median MR, and multivariable MR method was used to test the independent association of lipids with AAA risk. The association between AAA and SNPs in loci that can act as proxies for drug targets was also assessed. Data collection took place between January 9, 2015, and January 4, 2016. Data analysis was conducted between January 4, 2015, and December 31, 2016. Genetic elevation of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG). The association between genetic risk scores of lipid-associated SNPs and AAA risk, as well as the association between SNPs in lipid drug targets (HMGCR, CETP, and PCSK9) and AAA risk. Up to 4914 cases and 48 002 controls were included in our analysis. A 1-SD genetic elevation of LDL-C was associated with increased AAA risk (odds ratio [OR], 1.66; 95% CI, 1.41-1.96; P = 1.1 × 10-9). For HDL-C, a 1-SD increase was associated with reduced AAA risk (OR, 0.67; 95% CI, 0.55-0.82; P = 8.3 × 10-5), whereas a 1-SD increase in triglycerides was associated with increased AAA risk (OR, 1.69; 95% CI, 1.38-2.07; P = 5.2 × 10-7). In multivariable MR analysis and both MR-Egger and weighted median MR methods, the association of each lipid fraction with AAA risk remained largely unchanged. The LDL-C-reducing allele of rs12916 in HMGCR was associated with AAA risk (OR, 0.93; 95% CI, 0.89-0.98; P = .009). The HDL-C-raising allele of rs3764261 in CETP was associated with lower AAA risk (OR, 0.89; 95% CI, 0.85-0.94; P = 3.7 × 10-7). Finally, the LDL-C-lowering allele of rs11206510 in PCSK9 was weakly associated with a lower AAA risk (OR, 0.94; 95% CI, 0.88-1.00; P = .04), but a second independent LDL-C-lowering variant in PCSK9 (rs2479409) was not associated with AAA risk (OR, 0.97; 95% CI, 0.92-1.02; P = .28). The MR analyses in this study lend support to the hypothesis that lipids play an important role in the etiology of AAA. Analyses of individual genetic variants used as proxies for drug targets support LDL-C lowering as a potential effective treatment strategy for preventing and managing AAA. Show less

We conducted a meta-analysis of three endometrial cancer genome-wide association studies (GWAS) and two follow-up phases totaling 7,737 endometrial cancer cases and 37,144 controls of European ancestry. Genome-wide imputation and meta-analysis identified five new risk loci of genome-wide significance at likely regulatory regions on chromosomes 13q22.1 (rs11841589, near KLF5), 6q22.31 (rs13328298, in LOC643623 and near HEY2 and NCOA7), 8q24.21 (rs4733613, telomeric to MYC), 15q15.1 (rs937213, in EIF2AK4, near BMF) and 14q32.33 (rs2498796, in AKT1, near SIVA1). We also found a second independent 8q24.21 signal (rs17232730). Functional studies of the 13q22.1 locus showed that rs9600103 (pairwise r(2) = 0.98 with rs11841589) is located in a region of active chromatin that interacts with the KLF5 promoter region. The rs9600103[T] allele that is protective in endometrial cancer suppressed gene expression in vitro, suggesting that regulation of the expression of KLF5, a gene linked to uterine development, is implicated in tumorigenesis. These findings provide enhanced insight into the genetic and biological basis of endometrial cancer. Show less

To identify susceptibility loci for meningioma, we conducted a genome-wide association study of 859 affected individuals (cases) and 704 controls with validation in two independent sample sets totaling 774 cases and 1,764 controls. We identified a new susceptibility locus for meningioma at 10p12.31 (MLLT10, rs11012732, odds ratio = 1.46, P(combined) = 1.88 × 10(-14)). This finding advances our understanding of the genetic basis of meningioma development. Show less