Abstract
Background
The most common pathogenic transthyretin variant underlying variant transthyretin amyloidosis in the United States is c.424G>A, p.Val142Ile (V142I). In affected individuals, disease manifests predominantly as heart failure (HF) and cardiomyopathy (CM), with atrial fibrillation (AF) or atrial flutter (AFL), carpal tunnel syndrome (CTS), spinal stenosis (SS), and neuropathy also common.
Objectives
The aim of this study was to investigate the association of TTR V142I carrier status with these established outcomes.
Methods
A retrospective cohort study was conducted among individuals of African ancestry enrolled in the MVP (Million Veteran Program). Participants with at least 1 V142I allele were matched to control subjects on the basis of race, sex, and birth year. Outcomes included HF or CM, AF or AFL, CTS, SS, neuropathy, all-cause mortality, cardiovascular mortality, and HF-related hospitalization. Cumulative incidence and multivariable Cox proportional hazards regression models were used to compare V142I carriers with control subjects.
Results
The final study cohort included 2,658 V142I carriers and 13,459 matched control subjects. After multivariable adjustment, V142I carriers had significantly higher risks for HF or CM (HR: 1.20; 95% CI: 1.10-1.31), AF or AFL (HR: 1.26; 95% CI: 1.13-1.40), CTS (HR: 1.43; 95% CI: 1.30-1.57), SS (HR: 1.17; 95% CI: 1.07-1.28), and neuropathy (HR: 1.24; 95% CI: 1.13-1.36) compared with control subjects. A higher risk for HF or CM was observed among V142I carriers than matched control subjects with the following amyloidosis-related red-flag symptoms: AF or AFL (HR: 1.26; 95% CI: 1.03-1.52), CTS (HR: 1.40; 95% CI: 1.20-1.64), SS (HR: 1.26; 95% CI: 1.06-1.49), and neuropathy (HR: 1.28; 95% CI: 1.11-1.48). V142I carriers also had a significantly higher risk for all-cause mortality (HR: 1.12; 95% CI: 1.01-1.25), cardiovascular mortality (HR: 1.37; 95% CI: 1.14-1.65), and HF-related hospitalization (HR: 1.25; 95% CI: 1.07-1.45).
Conclusions
These findings highlight the systemic manifestations of variant transthyretin amyloidosis associated with the TTR V142I variant and underscore the need for increased awareness and earlier diagnostic efforts in high-risk populations.
Key Words: amyloidosis, atrial fibrillation, cardiomyopathy, carpal tunnel syndrome, genetics, neuropathy, spinal stenosis, V142I, variant transthyretin amyloidosis
Central Illustration
Transthyretin (TTR) is a tetrameric protein produced mainly by the liver that functions as a carrier for thyroxine and holo–retinol-binding protein.1 When the tetramer dissociates into monomers, misfolding and aggregation into beta-pleated sheets lead to disease through organ deposition.1 Pathogenic variants in the TTR gene can decrease tetramer stability, causing more rapid amyloid fibril formation.2,3 End-organ deposition of amyloid fibrils caused by pathogenic TTR variants is known as variant amyloidogenic TTR (ATTRv) amyloidosis.2,4 The most common TTR variant in the United States is c.424G>A, p.Val142Ile (V142I), in which isoleucine is substituted for valine at position 142 and which is inherited through an autosomal-dominant pathway. The V142I variant is found almost exclusively in individuals of African ancestry, with a prevalence of 3% to 4% in this population in the United States, and exhibits variable penetrance.5,6 Up to 10% of Black Americans with heart failure (HF) who are older than 60 years may be carriers of this variant.7
Traditionally, ATTRv amyloidosis due to the V142I variant has been thought to manifest predominantly as cardiomyopathy (CM).5,8 Other common manifestations of ATTRv amyloidosis occur in the musculoskeletal, nervous, and ocular systems.9 Carpal tunnel syndrome (CTS) is often an early symptom and has been observed in two-thirds of patients with clinically manifest ATTRv amyloidosis, and it may precede CM by 10 years.9,10 Additionally, neuropathy and spinal stenosis (SS) have been linked to both early and late onset of ATTRv amyloidosis.11 Onset of these red-flag symptoms before heart disease should prompt consideration of ATTRv amyloidosis in the differential diagnosis. ATTRv CM remains a substantially undiagnosed disease. When a diagnosis is made, it is often delayed. Life expectancy following CM manifestation ranges from 2 to 6 years.5,6,12
Although previous studies have associated the V142I variant with various cardiovascular outcomes, a comprehensive assessment of the full spectrum of ATTRv amyloidosis–related outcomes among V142I carriers remains unreported. This study provides a comprehensive analysis of the associations between carriers of the V142I variant and established amyloidosis-related outcomes within the Veterans Health Administration MVP (Million Veteran Program) (Central Illustration). These data may enhance early diagnostic strategies and inform clinical management and treatment approaches for this underdiagnosed condition.
Central Illustration.
Systemic Manifestations and Heart Failure Risk in Transthyretin V142I Variant Carriers
Comparison of clinical manifestations, heart failure/cardiomyopathy (HF/CM) risk, and outcomes between V142I carriers and matched non-carriers of African ancestry in the Million Veteran Program. (Left) V142I carriers had higher hazards of HF/CM, atrial fibrillation/atrial flutter (AF/AFL), carpal tunnel syndrome (CTS), spinal stenosis (SS), and neuropathy than matched non-carriers, reflecting the systemic nature and cardiovascular impact of V142I-associated ATTRv. (Right) Among individuals with AF/AFL, CTS, SS, or neuropathy, V142I carriers had higher subsequent hazards of HF/CM than non-carriers, highlighting these “red-flag” manifestations as potential triggers for earlier evaluation and diagnosis of ATTRv cardiac amyloidosis. TTR = transthyretin.
Methods
Regulatory approvals
Analyses of U.S. Department of Veterans Affairs (VA) national data were conducted under research protocols approved by the VA Salt Lake City institutional and scientific review boards, with a waiver of the requirement to obtain informed consent and a waiver of Health Insurance Portability and Accountability Act authorization. Analyses of MVP participant data were conducted as part of core and study-specific research protocols approved by the VA Central Institutional Review Board, with informed consent and Health Insurance Portability and Accountability Act authorization provided by MVP participants. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology reporting guidelines. Data used in this study cannot be shared publicly, because of VA policies on data privacy and security. Investigators with appropriate authorizations within the VA may request data access from the corresponding author.
Data sources
This retrospective cohort study used patient genetic data from the MVP, a large, multiethnic genetic biorepository of U.S. Veterans.13 Clinical data, both structured and unstructured, were extracted from the VA Corporate Data Warehouse, a data repository that provides longitudinal national electronic health record data for all Veterans receiving care. Data were also linked with Medicare and Medicaid records, allowing a more comprehensive assessment of health care use beyond the VA system. Data extraction for clinical outcomes was performed using International Classification of Diseases-Ninth Revision and International Classification of Diseases-10th Revision diagnostic codes and Current Procedural Terminology codes to identify relevant diagnoses and procedures. The National Death Index was used to assess cardiovascular and all-cause mortality. A complete list of codes used to define each variable is included in Supplemental Table 1.
TTR genotyping
Upon enrollment in the MVP, all participants provided blood samples for DNA extraction and genotyping. Genetic testing was conducted between 2011 and 2020, and results were used for research purposes only and were not available to clinicians. Details on the assay, quality control, and imputation of genotypes have been described previously.13 We extracted genotypes for rs76992529 (V142I) at chromosome 18:31,598,655(b38) from TopMed-imputed genomes and converted doses to hard genotype calls using PLINK version 1.07. Participants were identified on the basis of the number of TTR V142I alleles (ie, 0, 1, or 2 alleles).
Study population
As the TTR V142I variant is almost exclusively found in individuals with African ancestry, we limited our cohort to this population. Individuals were identified as being of African ancestry using either genetically inferred ancestry or harmonized ancestry and race/ethnicity.14,15 Among MVP participants with available genetic data and of African ancestry, we identified those with at least 1 V142I allele. Carriers were matched in a 1:5 ratio to noncarriers (no V142I alleles) of the same sex, birth year, and race. To allow at least 12.5 years of follow-up, we limited our cohort to patients who had at least 1 VA visit before January 1, 2008, which was considered baseline. Baseline characteristics were defined as measurements closest in time before January 1, 2008. The last date of follow-up was October 1, 2022.
Outcome definitions
The primary outcomes were the cumulative incidence of HF or CM, atrial fibrillation (AF) or atrial flutter (AFL), CTS, SS, and neuropathy. Secondary outcomes included HF-related hospitalization, cardiovascular mortality, and all-cause mortality. To identify HF or CM, AF or AFL, CTS, SS, and neuropathy, we queried VA and Medicare and Medicaid International Classification of Diseases and Current Procedural Terminology codes (Supplemental Table 1).We used the National Death Index to assess cardiovascular and all-cause mortality. A list of codes comprising the definitions of HF-related hospitalization and cardiovascular death is included in Supplemental Table 1.
Statistical analysis
Baseline characteristics were descriptively summarized for V142I allele carriers and matched control subjects. Continuous variables are reported as median (Q1-Q3) and categorical variables as frequencies and percentages. The Kruskal-Wallis test was used to compare continuous variables and the chi-square test to compare categorical variables. To ascertain risk for outcomes over the study period, we calculated cumulative incidence estimates with 95% CIs and plotted the corresponding curves (using the cuminc function in R [R Foundation for Statistical Computing]). Time to event was defined from January 1, 2008, to the first diagnosis code for the event of interest. When assessing the risk for HF or CM after prior red-flag symptoms (AF or AFL, CTS, SS, and neuropathy), the start time was defined as the first diagnosis code for the red-flag condition and the end time as the first diagnosis code for HF or CM. When plotting the cumulative incidence of cardiovascular and all-cause mortality, the index date was defined as time of MVP enrollment to avoid including an immortal time period between January 1, 2008, and MVP enrollment in the cumulative incidence functions. To show cumulative risk over the life course, cumulative incidence functions were plotted for each outcome with start time defined as age 0 and end time as age at event. For nonfatal outcomes, death was treated as a competing event to account for the possibility that individuals may die before experiencing the outcome of interest.16 Cumulative incidence curves were compared using Gray’s test for competing risk outcomes and the log-rank test for all-cause mortality. Participants who had experienced outcomes before the index date were excluded from the analysis.
We used cause-specific multivariable Cox proportional hazards regression, censoring participants at the time of death, to compare hazards for outcomes between V142I carriers and control subjects. Covariates included V142I carrier status, age, sex, type 2 diabetes, hypertension diagnosis, body surface area (continuous), and smoking status. Matched variables were retained in the models to account for any residual confounding within matched groups. Time scales for the models were defined as follows: January 1, 2008, to first diagnosis of the outcome event; from first diagnosis of a red-flag symptom (AF or AFL, CTS, SS, or neuropathy) to first diagnosis of HF or CM; and time from MVP enrollment to death. Participants who had experienced outcomes before the index date were excluded from multivariable analysis. Results from Cox models are presented as HRs with 95% CIs. All computations were conducted using R version 4.4.2.
Results
Among 658,582 MVP participants with available genetic data, 123,249 participants were of African ancestry. We identified 3,887 (3.2%) who carried at least 1 V142I allele, including 22 (0.02% of those of African ancestry) with 2 alleles. After excluding participants with missing first VA visit date or demographic information and those whose first VA visit occurred after 2008, a total of 2,658 V142I carriers and 13,459 matched control subjects were included in the final study cohort (Figure 1).
Figure 1.
Flowchart of Study Cohort Selection
This figure illustrates the sequential steps used to derive the analytical cohort from the MVP (Million Veteran Program). VA = U.S. Department of Veterans Affairs (VA).
Baseline characteristics
Among the included participants, 5 V142I carriers (0.2%) and 16 control subjects (0.1%) had fewer than 10 visits within the Veterans Health Administration during the study period. The median age of V142I carriers was 53 years (Q1-Q3: 46-60 years), and 87.2% (n = 2,317) were men. Among V142I carriers at baseline, 164 (6.2%) had HF, 81 (3.0%) had AF or AFL, 1,595 (60.0%) had hypertension, and 689 (25.9%) had type 2 diabetes. Clinical characteristics were generally similar between V142I carriers and control subjects. The remaining baseline clinical characteristics of the study population, stratified by carrier status, are presented in Table 1.
Table 1.
Baseline Characteristics of Patients With African Ancestry, Stratified by V142I Carrier Status, and Matched Control Subjects
| Total (N = 16,117) | V142I Carriers (n = 2,658) | Matched Controls (n = 13,459) | P Value | |
|---|---|---|---|---|
| Demographics | ||||
| Age, y | 53 (46-60) | 53 (46-60) | 53 (46-60) | 0.89 |
| Female | 2,067 (12.8) | 341 (12.8) | 1,726 (12.8) | >0.99 |
| Smoking status | 0.82 | |||
| Current | 2,590 (16.1) | 432 (16.3) | 2,158 (16.0) | |
| Former | 8,863 (55.0) | 1,466 (55.2) | 7,397 (55.0) | |
| Never | 4,123 (25.6) | 665 (25.0) | 3,458 (25.7) | |
| Unknown | 541 (3.4) | 95 (3.6) | 446 (3.3) | |
| Clinical characteristics | ||||
| Physical examination | ||||
| Systolic blood pressure, mm Hg | (n = 16,074) | (n = 2,649) | (n = 13,425) | |
| 133 (122-145) | 132.0 (121.0-144.0) | 133.0 (122.0-145.0) | 0.048 | |
| Diastolic blood pressure, mm Hg | (n = 16,064) | (n = 2,649) | (n = 13,415) | |
| 81 (73-89) | 80 (73.0-89.0) | 81 (73.0-89.0) | 0.087 | |
| BMI, kg/m2 | (n = 15,567) | (n = 2,571) | (n = 12,996) | |
| 30.99 (27.25-35.26) | 31 (27.16-35.44) | 30.99 (27.26-35.24) | 0.97 | |
| Body surface area, m2 | (n = 16,040) | (n = 2,642) | (n = 13,398) | |
| 2.10 (1.94-2.25) | 2.09 (1.95-2.25) | 2.09 (1.94-2.25) | 0.84 | |
| Comorbidities | ||||
| Heart failure | 933 (5.8) | 164 (6.2) | 769 (5.7) | 0.38 |
| Atrial fibrillation/atrial flutter | 425 (2.6) | 81 (3.0) | 344 (2.6) | 0.17 |
| Hypertension | 9,810 (60.9) | 1,595 (60.0) | 8,215 (61.0) | 0.33 |
| Type II diabetes mellitus | 4,232 (26.3) | 689 (25.9) | 3,543 (26.3) | 0.68 |
| Amyloidosis-related symptoms | ||||
| Carpal tunnel syndrome | 1,485 (9.2) | 247 (9.3) | 1,238 (9.2) | 0.91 |
| Spinal stenosis | 954 (5.9) | 171 (6.4) | 783 (5.8) | 0.24 |
| Neuropathy | 1,371 (8.5) | 238 (9.0) | 1,133 (8.4) | 0.39 |
| Echocardiographic parameters | ||||
| LVEF, % | (n = 4,904) | (n = 827) | (n = 4,077) | |
| 59 (52.0-65.0) | 58.70 (51.0-65.0) | 59.0 (52.0-65.0) | 0.65 |
Values are median (Q1-Q3) or n (%).
BMI = body mass index; LVEF = left ventricular ejection fraction.
Clinical diagnosis of amyloidosis
During follow-up, 88 V142I carriers (3.3%) and 59 control subjects (0.4%) were clinically diagnosed with amyloidosis (P < 0.001). The median age at diagnosis was 74 years (Q1-Q3: 69-78 years) for carriers and 70 years (Q1-Q3: 64-75 years) for control subjects (P = 0.610). Prior to or at the time of diagnosis, HF or CM was present in 73 carriers (83.0%) and 29 control subjects (49.2%) (P < 0.001), AF or AFL in 34 (38.6%) and 11 (18.6%) (P = 0.017), CTS in 59 (67.0%) and 10 (16.9%) (P < 0.001), SS in 24 (27.3%) and 17 (28.8%) (P = 0.987), and neuropathy in 33 (37.5%) and 15 (25.4%) (P = 0.177), respectively.
Cumulative incidence of amyloidosis-related clinical outcomes
Across all amyloidosis-related outcomes, cumulative incidence was significantly higher among carriers than control subjects (P < 0.001 for all comparisons, Gray’s test). For HF or CM, rates among carriers and control subjects at 5, 10, and 12.5 years of follow-up were 6.4% (95% CI: 5.4%-7.3%) and 6.0% (95% CI: 5.6%-6.5%), 18.1% (95% CI: 16.6%-19.6%) and 16.4% (95% CI: 15.7%-17.0%), and 24.6% (95% CI: 22.9%-26.3%) and 21.7% (95% CI: 20.9%-22.4%), respectively (Figure 2A). For AF or AFL, rates among carriers and control subjects at 5, 10, and 12.5 years of follow-up were 3.5% (95% CI: 2.7%-4.2%) and 2.9% (95% CI: 2.6%-3.2%), 10.9% (95% CI: 9.7%-12.1%) and 9.1% (95% CI: 8.6%-9.6%), and 14.6% (95% CI: 13.2%-15.9%) and 12.5% (95% CI: 11.9%-13.0%), respectively (Figure 2B). For CTS, rates among carriers and control subjects at 5, 10, and 12.5 years of follow-up were 10.2% (95% CI: 9.0%-11.4%) and 7.2% (95% CI: 6.8%-7.7%), 19.3% (95% CI: 17.7%-20.9%) and 14.1% (95% CI: 13.4%-14.7%), and 22.7% (95% CI: 21.0%-24.4%) and 16.6% (95% CI: 15.9%-17.3%), respectively (Figure 2C). For SS, rates among carriers and control subjects at 5, 10, and 12.5 years of follow-up were 7.1% (95% CI: 6.1%-8.1%) and 6.7% (95% CI: 6.3%-7.2%), 19.4% (95% CI: 17.9%-21.0%) and 16.8% (95% CI: 16.2%-17.5%), and 23.8% (95% CI: 22.2%-25.5%) and 20.9% (95% CI: 20.2%-21.6%), respectively (Figure 2D). For neuropathy, rates among carriers and control subjects at 5, 10, and 12.5 years of follow-up were 11.5% (95% CI: 10.2%-12.7%) and 9.8% (95% CI: 9.3%-10.3%), 20.8% (95% CI: 19.2%-22.5%) and 17.4% (95% CI: 16.8%-18.1%), and 24.1% (95% CI: 22.4%-25.8%) and 20.2% (95% CI: 19.5%-20.9%), respectively (Figure 2E).
Figure 2.
Cumulative Incidence of Clinical Outcomes by V142I Carrier Status
Cumulative incidence curves for clinical outcomes by years of study follow-up (A-E) and by age (F-J), stratified by V142I carrier status: (A,F) heart failure or cardiomyopathy, (B,G) atrial fibrillation (AF) or atrial flutter (AFL), (C,H) carpal tunnel syndrome, (D,I) spinal stenosis, and (E,J) neuropathy.
These differences persisted after adjustment in a multivariable Cox regression model. Compared with control subjects, carriers had a significantly higher risk for developing HF or CM (HR: 1.20; 95% CI: 1.10-1.31), AF or AFL (HR: 1.26; 95% CI: 1.13-1.40), CTS (HR: 1.43; 95% CI: 1.30-1.57), SS (HR: 1.17; 95% CI: 1.07-1.28), and neuropathy (HR: 1.24; 95% CI: 1.13-1.36) (Table 2). HRs for all variables included in the multivariable models are presented in Supplemental Table 2A.
Table 2.
Multivariable Cox Regression Analysis Evaluating the Risk of V142I Carriers for Developing the Studied Outcomes
| HR | 95% CI | P Value | |
|---|---|---|---|
| HF/CM | 1.20 | 1.10-1.31 | <0.001 |
| AF/AFL | 1.26 | 1.13-1.40 | <0.001 |
| CTS | 1.43 | 1.30-1.57 | <0.001 |
| SS | 1.17 | 1.07-1.28 | <0.001 |
| Neuropathy | 1.24 | 1.13-1.36 | <0.001 |
Adjusted for age, sex, type 2 diabetes, hypertension, body surface area, and smoking status.
AF = atrial fibrillation; AFL = atrial flutter; CM = cardiomyopathy; CTS = carpal tunnel syndrome; HF = heart failure; SS = spinal stenosis.
To further assess age-related effects on outcomes, we evaluated cumulative incidence at ages 70, 80, and 90 years of age. At each age, cumulative incidence remained significantly higher among carriers than control subjects (P < 0.001 for all comparisons, Gray’s test). For HF or CM, rates among carriers and control subjects at 70, 80, and 90 years of age were 30.9% (95% CI: 28.8%-33.1%) and 29.3% (95% CI: 28.3%-30.2%), 54.9% (95% CI: 51.5%-58.4%) and 45.9% (95% CI: 44.5%-47.3%), and 79.1% (95% CI: 74.6%-83.5%) and 63.8% (95% CI: 61.6%-66.0%), respectively (Figure 2F). For AF or AFL, rates among carriers and control subjects at 70, 80, and 90 years of age were 18.9% (95% CI: 17.0%-20.7%) and 15.4% (95% CI: 14.7%-16.2%), 36.2% (95% CI: 32.8%-39.6%) and 28.2% (95% CI: 26.9%-29.5%), and 54.9% (95% CI: 49.3%-60.5%) and 44.0% (95% CI: 41.6%-46.3%), respectively (Figure 2G). For CTS, rates among carriers and control subjects at 70, 80, and 90 years of age were 32.7% (95% CI: 30.6%-34.8%) and 27.0% (95% CI: 26.2%-27.9%), 46.5% (95% CI: 43.4%-49.6%) and 32.5% (95% CI: 31.4%-33.5%), and 49.6% (95% CI: 45.8%-53.3%) and 35.0% (95% CI: 33.6%-36.3%), respectively (Figure 2H). For SS, rates among carriers and control subjects at ages 70, 80, and 90 years of age were 31.8% (95% CI: 29.8%-33.9%) and 28.7% (95% CI: 27.8%-29.6%), 42.6% (95% CI: 39.9%-45.4%) and 38.0% (95% CI: 36.8%-39.2%), and 46.2% (95% CI: 42.8%-49.7%) and 43.2% (95% CI: 41.6%-44.9%), respectively (Figure 2I). For neuropathy, rates among carriers and control subjects at 70, 80, and 90 years of age were 35.6% (95% CI: 33.5%-37.8%) and 30.1% (95% CI: 29.2%-31.0%), 44.8% (95% CI: 42.0%-47.7%) and 39.1% (95% CI: 37.9%-40.3%), and 50.3% (95% CI: 46.1%-54.5%) and 44.5% (95% CI: 42.8%-46.3%), respectively (Figure 2J).
Development of HF or CM after red-flag symptoms
We evaluated the risk for HF or CM from the time of first diagnosis of amyloidosis-related red-flag symptoms (ie, AF or AFL, CTS, SS, and neuropathy). Among individuals with AF or AFL, HF or CM rates among carriers and control subjects at 5, 10, and 12.5 years after AF or AFL diagnosis were 35.7% (95% CI: 29.5%-41.8%) and 31.4% (95% CI: 28.6%-34.2%), 51.4% (95% CI: 44.4%-58.4%) and 42.7% (95% CI: 39.4%-46.0%), and 59.2% (95% CI: 51.7%-66.7%) and 46.9% (95% CI: 43.4%-50.4%), respectively (Figure 3A). The median time from AF or AFL diagnosis to HF or CM was 2.42 years (Q1-Q3: 0.44-6.60 years). Among individuals with CTS, HF or CM rates among carriers and control subjects at 5, 10, and 12.5 years after CTS diagnosis were 10.6% (95% CI: 8.3%-13.0%) and 7.9% (95% CI: 7.0%-8.9%), 24.2% (95% CI: 20.7%-27.8%) and 16.7% (95% CI: 15.2%-18.1%), and 29.1% (95% CI: 25.2%-33.0%) and 22.1% (95% CI: 20.4%-23.8%), respectively (Figure 3B). The median time from CTS diagnosis to HF or CM was 6.98 years (Q1-Q3: 3.33-11.37 years). Among individuals with SS, HF or CM rates among carriers and control subjects at 5, 10, and 12.5 years after SS diagnosis were 12.3% (95% CI: 9.7%-14.8%) and 10.4% (95% CI: 9.3%-11.5%), 25.3% (95% CI: 21.4%-29.2%) and 19.6% (95% CI: 18.0%-21.3%), and 31.5% (95% CI: 27.0%-35.9%) and 25.7% (95% CI: 23.7%-27.7%), respectively (Figure 3C). The median time from SS diagnosis to HF or CM was 5.66 years (Q1-Q3: 2.52-9.73 years). Among individuals with neuropathy, HF or CM rates among carriers and control subjects at 5, 10, and 12.5 years after neuropathy diagnosis were 14.7% (95% CI: 12.0%-17.4%) and 12.9% (95% CI: 11.7%-14.1%), 28.5% (95% CI: 24.9%-32.1%) and 22.8% (95% CI: 21.2%-24.4%), and 32.8% (95% CI: 28.9%-36.8%) and 27.9% (95% CI: 26.1%-29.7%), respectively (Figure 3D). The median time from neuropathy diagnosis to HF or CM was 6.06 years (Q1-Q3: 2.77-10.23 years).
Figure 3.
Cumulative Incidence of HF or CM Following Amyloidosis Red-Flag Symptoms
Cumulative incidence of heart failure (HF) or cardiomyopathy (CM) from the time of first diagnosis of amyloidosis-related red-flag symptoms, stratified by V142I carrier status: (A) AF or AFL, (B) carpal tunnel syndrome (CTS), (C) spinal stenosis (SS), and (D) neuropathy. Abbreviations as in Figure 2.
After adjustment in multivariable Cox proportional hazards models, V142I carriers had a significantly higher risk for developing HF or CM than control subjects among patients with AF or AFL (HR: 1.26; 95% CI: 1.03-1.52), CTS (HR: 1.40; 95% CI: 1.20-1.64), SS (HR: 1.26; 95% CI: 1.06-1.49), or neuropathy (HR: 1.28; 95% CI: 1.11-1.48) (Table 3). HRs for all variables included in the multivariable models are presented in Supplemental Table 2B.
Table 3.
Multivariable Cox Regression Analysis Evaluating the Risk for Developing HF or CM Following the Onset of Amyloidosis-Related Red-Flag Symptoms
| HR | 95% CI | P Value | |
|---|---|---|---|
| From AF/AFL to HF/CM | 1.26 | 1.03-1.52 | 0.021 |
| From CTS to HF/CM | 1.40 | 1.20-1.64 | <0.001 |
| From SS to HF/CM | 1.26 | 1.06-1.49 | 0.008 |
| From neuropathy to HF/CM | 1.28 | 1.11-1.48 | <0.001 |
Adjusted for age, sex, type 2 diabetes, hypertension, body surface area, and smoking status.
Abbreviations as in Table 2.
Carrier status and risk for hospitalizations and mortality
V142I carriers had a significantly higher risk for all-cause mortality (HR: 1.12; 95% CI: 1.01-1.25), cardiovascular mortality (HR: 1.37; 95% CI: 1.14-1.65), and HF-related hospitalization (HR: 1.25; 95% CI: 1.07-1.45) compared with control subjects (Table 4, Supplemental Table 2C, Supplemental Figures 1A to 1C). The difference in cumulative incidence estimates between carriers and control subjects increased over the study follow-up for all outcomes.
Table 4.
Multivariable Cox Regression Analysis Evaluating the Risk for All-Cause Mortality, Cardiovascular Mortality, and HF Hospitalizations
| HR | 95% CI | P Value | |
|---|---|---|---|
| All-cause mortality | 1.12 | 1.01-1.25 | 0.030 |
| Cardiovascular mortality | 1.37 | 1.14-1.65 | <0.001 |
| Heart failure hospitalizations | 1.25 | 1.07-1.45 | 0.004 |
Adjusted for age, sex, type 2 diabetes, hypertension, body surface area, and smoking status.
For all-cause mortality, cumulative incidence among carriers and control subjects at ages 70, 80, and 90 years of age was 12.6% (95% CI: 11.0%-14.2%) and 12.2% (95% CI: 11.5%-13.0%), 35.2% (95% CI: 31.5%-39.0%) and 27.5% (95% CI: 26.0%-28.9%), and 66.2% (95% CI: 58.5%-73.9%) and 57.6% (95% CI: 54.5%-60.8%), respectively (P < 0.001, log-rank test) (Supplemental Figure 1D). For cardiovascular mortality, cumulative incidence among carriers and control subjects at 70, 80, and 90 years of age was 4.5% (95% CI: 3.5%-5.5%) and 3.4% (95% CI: 3.0%-3.8%), 13.8% (95% CI: 11.0%-16.6%) and 7.8% (95% CI: 6.9%-8.6%), and 28.8% (95% CI: 20.1%-37.4%) and 21.3% (95% CI: 18.1%-24.4%), respectively (P < 0.001, Gray’s test) (Supplemental Figure 1E). Finally, the cumulative incidence of HF-related hospitalization among carriers and control subjects at 70, 80, and 90 years of age was 7.2% (95% CI: 5.9%-8.4%) and 7.0% (95% CI: 6.4%-7.5%), 18.1% (95% CI: 15.3%-20.8%) and 13.4% (95% CI: 12.5%-14.4%), and 31.7% (95% CI: 26.0%-37.3%) and 22.7% (95% CI: 20.7%-24.6%), respectively (P = 0.016, Gray’s test) (Supplemental Figure 1F).
Discussion
We investigated whether the V142I variant is a risk factor for HF or CM and other common clinical manifestations of ATTRv amyloidosis. This large cohort enabled robust evaluation of ATTRv amyloidosis–related clinical features in a real-world population and provided insight into genotype-phenotype correlations for the V142I variant. The prevalence of the TTR V142I pathogenic variant among Veterans of African ancestry was 3.2%, comparable with the prevalence reported in other cohorts.7,12,17, 18, 19 Key findings of our study include the following: 1) increased cumulative incidence of HF or CM, AF or AFL, CTS, SS, and neuropathy in carriers of the V142I variant compared with noncarriers; 2) a higher incidence of HF or CM among carriers who developed amyloidosis-related red-flag symptoms; and 3) increased risk for hospitalization and mortality in V142I carriers (Central Illustration).
Similar to prior studies demonstrating that V142I carriers have an increased risk for adverse cardiovascular outcomes,7,12,18, 19, 20 we observed a significantly higher risk for HF or CM in carriers after multivariable adjustment (HR: 1.20; 95% CI: 1.10-1.31), with cumulative incidence increasing with age. By 12.5 years of follow-up, the cumulative incidence of HF or CM was 24.6% (95% CI: 22.9%-26.3%) in V142I carriers compared with 21.7% (95% CI: 20.9%-22.4%) in noncarriers. By 80 years of age, the cumulative incidence of HF or CM was 54.9% (95% CI: 51.5%-58.4%) in carriers vs 45.9% (95% CI: 44.5%-47.3%) in noncarriers. These higher cumulative incidences support previous observations of a greater phenotypic penetrance of progressive cardiac amyloidosis with increasing age and highlight the impact of the V142I variant on cardiovascular health.7,12,18,19 Our results also complement a recent study from the All of Us cohort reporting increased lifetime risk for HF and AF among V142I carriers.20 Although that study provided population-level insights, our matched-control VA cohort with up to 15 years of follow-up extends these findings by incorporating systemic manifestations, temporal relationships between red-flag symptoms and HF or CM onset, and long-term mortality and hospitalization outcomes, providing a more comprehensive characterization of the disease phenotype and its association with clinical outcomes.
Orthopedic manifestations of wild-type ATTR (ATTRwt) amyloidosis, including CTS and SS, have been well described, with CTS reported in more than 50% of cases.8,21 Data on ATTRv amyloidosis are more limited, but CTS has been observed in 24% to 30% of cases22, 23, 24, 25 and identified as an early clinical manifestation of ATTRv amyloidosis.9,25,26 SS is another established noncardiac manifestation of ATTRwt amyloidosis that remains understudied in ATTRv amyloidosis. Several studies have examined the relationship between amyloid deposition in the spinal canal and systemic ATTR amyloidosis manifestations, including CM.27,28 Reports on orthopedic manifestations of amyloidosis suggest that at the time of SS intervention, patients with amyloidotic ligamentum flavum hypertrophy are only slightly more likely to have cardiac amyloidosis than those without pathologic TTR deposition.29 However, the high rates of SS and CTS in this V142I cohort suggest a stronger association between these musculoskeletal complications and the V142I variant, with cumulative incidence by 80 years of age of 46.5% (95% CI: 43.4%-49.6%) for CTS and 42.6% (95% CI: 39.9%-45.4%) for SS. These findings indicate that orthopedic manifestations may be more prevalent in V142I carriers than previously appreciated and further underscore the systemic nature of V142I ATTRv amyloidosis and its association with adverse outcomes.
To our knowledge, this study provides novel insight into the temporal relationship between amyloidosis-related red-flag symptoms and the subsequent development of HF or CM, with V142I carriers who developed AF or AFL, CTS, SS, or neuropathy having higher adjusted risks for HF or CM (HRs of 1.26, 1.40, 1.26, and 1.28, respectively). We observed a marked increase in HF or CM diagnosis approximately 10 years after the diagnosis of CTS, mirroring findings from retrospective studies in patients with ATTRwt amyloidosis. The development of CTS may represent one of the earliest clinical manifestations in carriers of TTR pathogenic variants with a predominant cardiac phenotype, and greater recognition of this association could support clearer screening strategies to detect incipient myocardial involvement.9,25
Neuropathy is another prevalent clinical manifestation of ATTRv amyloidosis, most frequently associated with variants other than V142I.30 Although V142I has historically been characterized by a predominantly cardiac phenotype, prior work has suggested an increased risk for neuropathy among carriers.6 Our study supports this association, showing that neuropathy is more prevalent in V142I carriers than in noncarriers, consistent with a multisystem impact of this variant. Additionally, among patients who developed neuropathy, V142I carriers had a higher subsequent risk for HF or CM than control subjects, underscoring the link between neurologic and cardiac involvement in this population.
Data on mortality differences between V142I carriers and noncarriers are limited and conflicting; some studies have suggested an increased risk, whereas others have not.17, 18, 19 In our analysis, which leveraged a larger sample size and long-term follow-up, V142I carriers had higher risks for all-cause and cardiovascular mortality than did noncarriers. Notably, cumulative incidence of HF-related hospitalization and cardiovascular mortality was higher among V142I carriers than noncarriers, reflecting the substantial burden of cardiac complications in this population. Taken together, these findings support the V142I variant as an important genetic contributor to morbidity and mortality, largely through its impact on cardiovascular health.
TTR cardiac amyloidosis is substantially underdiagnosed, and diagnosis is often delayed.12 In our study, genetic results were used for research purposes only and were not available to clinicians, highlighting the gap between genetic prevalence and clinical diagnosis. Notably, only 88 V142I carriers (3.3%) and 59 control subjects (0.4%) had a clinical diagnosis of amyloidosis, despite a significant burden of morbidities known to be associated with the disease. These findings highlight multiple opportunities to improve early detection of ATTRv cardiac amyloidosis.
The presence of orthopedic, neuropathic, and arrhythmic manifestations before the onset of HF or CM creates an opportunity to detect ATTRv cardiac amyloidosis earlier and to initiate disease-modifying therapy at a less advanced stage.31 In addition to improving disease awareness among clinicians, novel strategies will likely be required to identify affected patients earlier in the disease course. For example, incorporating red-flag symptoms into electronic health record systems and developing automated clinical alerts for high-risk patients could enable earlier recognition, more precise diagnosis, and timely initiation of treatment. Incorporating data on symptom timing and progression into predictive models may further improve their ability to identify evolving risk trajectories and optimize the timing of screening.
Previously proposed prognostic algorithms for early disease screening have incorporated clinical, imaging, laboratory, genetic, and histopathologic variables.10,32 However, these studies were based on relatively small patient cohorts. To develop predictive models with higher accuracy, larger data sets and machine learning approaches are likely needed. Such models could support closer monitoring and earlier intervention, potentially improving outcomes by enabling therapy initiation at an earlier disease stage.31 Further prospective studies should explore the clinical impact of early intervention in V142I ATTRv amyloidosis and assess whether these diagnostic strategies reduce symptom progression and improve survival.
Study limitations
As with all studies using observational electronic health record data, our analyses are subject to potential inaccuracies related to incomplete data capture, coding inconsistencies, and misclassification of diagnoses. Although V142I carriers were matched with control subjects by age, sex, and race, unmeasured confounders could still have influenced the observed associations. We included patients whose first VA visit occurred before 2008 and who subsequently enrolled in the MVP between 2011 and 2020; patients who died before MVP enrollment were therefore not included in the study cohort, which may have led to underestimation of mortality, particularly in the carrier group. Although type 2 diabetes was adjusted for in multivariable analyses, residual confounding cannot be excluded, and some cases of neuropathy among V142I carriers may reflect diabetic rather than amyloid-related neuropathy. Phenotypic overlap among V142I carriers was assessed using crude descriptive comparisons (Supplemental Tables 3A to 3D); time-dependent analyses to assess the temporal sequence of disease manifestations were beyond the scope of this study. Rates of CTS and SS were notably high among V142I carriers with neuropathy (Supplemental Table 3D), which may reflect both true shared pathophysiology and potential diagnostic misclassification due to overlapping neurocompressive symptoms. Finally, despite the large number of visits and the long follow-up, analyses may be influenced by loss to follow-up or outcomes recorded outside the Veterans Health Administration; however, this limitation is partially mitigated by linkage to Medicare and Medicaid data.
Conclusions
This study provides important insights into the clinical impact of the TTR V142I variant in a large national cohort of Veterans, highlighting increased risks for HF or CM, AF or AFL, CTS, SS, and neuropathy, as well as elevated risks for HF-related hospitalization and mortality among carriers. These findings emphasize the systemic nature of V142I ATTRv amyloidosis and underscore the need for earlier diagnostic efforts in high-risk populations. Future studies should focus on prospective cohorts, more racially and ethnically diverse populations, and refined predictive models to enhance early detection and optimize disease management. Early diagnosis and targeted interventions may help reduce symptom progression and improve quality of life for individuals with this variant.
Perspectives.
COMPETENCY IN MEDICAL KNOWLEDGE: Among Veterans of African ancestry, carriers of the TTR V142I variant have higher cumulative incidence of HF or CM, AF or AFL, CTS, SS, neuropathy, HF-related hospitalization, and mortality than matched control subjects, highlighting a systemic, age-related ATTRv amyloidosis phenotype in which musculoskeletal, neuropathic, and arrhythmic manifestations often precede overt HF or CM.
TRANSLATIONAL OUTLOOK: Future research should evaluate targeted screening strategies that leverage red-flag manifestations to identify V142I carriers earlier in the disease course and test whether earlier diagnosis and initiation of disease-modifying therapy can improve survival and quality of life in this high-risk population.
Funding Support and Author Disclosures
This research is based on data from the Million Veteran Program, Office of Research and Development, Veterans Health Administration, and was supported by MVP000 as well as award I01-BX003362. We thank the Veterans who generously agreed to participate in the Million Veteran Program. This work was supported using resources and facilities of the VA Informatics and Computing Infrastructure, including data analytics conducted by its precision medicine research team, which is funded under the research priority to Put VA Data to Work for Veterans (VA ORD 24-D4V-02). This publication does not represent the views of the VA or the U.S. government. Dr Lynch, Dr Teerlink, Mr Nelson, Dr Ferraro, Mr Agiri, and Ms Pridgen have received grants from Alnylam Pharmaceuticals, Astellas Pharma, AstraZeneca Pharmaceuticals, Biodesix, Celgene, Cerner Enviza, GlaxoSmithKline, IQVIA, Janssen Pharmaceuticals, Novartis International, and Parexel International through the University of Utah or the Western Institute for Veterans Research, outside the submitted work. Dr Stehlik serves as a consultant to Natera, Medtronic, and TransMedics; and has received research support from Natera and Merck. Dr Carter has served as a consultant to Pfizer, BridgeBio, and Alnylam. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.
Footnotes
Ronald Witteles, MD, Deputy Editor, served as Acting Editor-in-Chief for this paper.
The authors attest they are in compliance with human studies committees and animal welfare regulations of the authors’ institutions and Food and Drug Administration guidelines, including patient consent where appropriate. For more information, visit the Author Center.
Appendix
For supplemental methods, tables, and a figure, please see the online version of this paper.
Appendix
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