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. Author manuscript; available in PMC: 2026 Jun 23.
Published in final edited form as: J Gerontol B Psychol Sci Soc Sci. 2026 Jul 1;81(8):gbag105. doi: 10.1093/geronb/gbag105

Purpose in life and blood-based biomarkers of brain health

Angelina R Sutin 1, Martina Luchetti 1, Yannick Stephan 2, Antonio Terracciano 1
PMCID: PMC13286235  NIHMSID: NIHMS2185671  PMID: 42281408

Abstract

Objectives:

Purpose in life is associated consistently with better cognitive outcomes. The association between purpose and neurobiomarkers of brain health has been less robust than the association with cognitive outcomes. This research uses the largest sample to date to test the association between purpose in life and four neurobiomarkers of brain health measured from plasma: The Aβ42/Aβ40 ratio, p-tau181, neurofilament light (NfL), and glial fibrillary acidic protein (GFAP). We further test whether higher purpose is associated with cognitive resilience against neuropathological burden (i.e., better cognitive performance relative to the amount of neuropathology).

Methods:

Data were from the Health and Retirement Study. Participants (N=4193; Mage=68.87, SD=10.17) reported on their purpose in life and provided venous blood. Biomarkers were assessed using Quanterix’s Simoa platforms. Linear regression tested the association between purpose and the four neurobiomarkers. Residual and interaction-based approaches evaluated cognitive resilience.

Results:

Purpose in life was associated with lower NfL accounting for sociodemographic factors (β=−.06, p<.001). Clinical and behavioral covariates accounted for half of this association, but it persisted (β=−.03, p=.007). Purpose was unrelated to the other three neurobiomarkers. Purpose in life was associated with greater cognitive resilience when tested with the residual approach (β=.12, p<.001) but not the interaction approach (βinteraction=.01, p=.372).

Discussion:

In the largest sample to date, individuals with more purpose in life had less neuronal injury, as measured with NfL. Purpose was unrelated to other common neurobiomarkers of brain health.

Keywords: purpose in life, neuropathology, resilience, neuronal injury, well-being

Purpose in life, the feeling that one’s life is goal-oriented and has direction (Ryff, 1989), is associated consistently with better cognitive health (Sutin et al., 2021), including better performance on tasks that measure episodic memory, verbal fluency, and processing speed (Estrella et al., 2021; Sutin, Luchetti, Stephan, et al., 2023b; Zahodne et al., 2018). Purpose is also associated with healthier cognitive outcomes in older adulthood: Among individuals who are cognitively healthy, greater purpose in life is associated with lower risk of incident Alzheimer’s disease and related dementias (ADRD) and other neurodegenerative diseases (e.g., Parkinson’s disease), associations that are well-replicated (Boyle et al., 2010; Okuzono et al., 2022; Sutin, Luchetti, Aschwanden, et al., 2023; Sutin et al., 2024).

The literature on purpose in life and cognitive health has focused primarily (although not exclusively) on cognitive function measured with performance tasks and clinical evaluations of cognitive function (e.g., diagnosis of Alzheimer’s disease). There are also other measures of brain health indicative of ADRD. The ATN framework of Alzheimer’s disease, for example, characterizes the disease by the presence of amyloid (A), tau (T), and/or neurodegeneration (N) (Jack et al., 2018). Neuroinflammation has been added to the framework as an important but nonspecific indicator of the disease (Heneka et al., 2025). Advances in technology have made it possible to measure markers of the ATN framework from blood. Specifically, the ratio of Aβ42/Aβ40 is a marker of accumulation of beta-amyloid (Aβ) plaques and p-tau181 is a marker of hyperphosphorylated-tau neurofibrillary tangles. These neurobiomarkers reflect key neural signatures of Alzheimer’s disease. Neurofilament light (NfL) is a measure of neuronal injury and glial fibrillary acidic protein (GFAP) is a measure of astrogliosis and neuroinflammation. NfL is correlated with neurodegeneration measured through neuroimaging (Khalil et al., 2018), and GFAP is related to neural degeneration (Abdelhak et al., 2022). NfL and GFAP are not specific to Alzheimer’s disease but have been implicated in it and are thus considered ADRD-related markers of brain health (Cronjé et al., 2023). These markers are apparent in blood even before the onset of cognitive symptoms (Estepp et al., 2023; Grande et al., 2025).

There is a small literature on well-being and neurobiomarkers that suggests little to no association with these markers of brain health. Studies from the Rush Memory and Aging Project (MAP) have found either no association between purpose in life and amyloid or tau measured in the brain at autopsy (n=246; Boyle et al., 2012) or the expected negative association between eudaimonic well-being (a well-being index that included purpose in life; the association between purpose alone and neuropathology was not reported) and beta-amyloid but no association with neurofibrillary tangles at autopsy (n=348; Willroth et al., 2023). An analysis of a subsample from the UK Biobank on the related construct of meaning in life found no association with these four neurobiomarkers (Aβ42/Aβ40, p-tau181, NfL, GFAP) measured from blood (n=1150; Sutin et al., 2025).

Although this literature is not promising, there are several reasons why the current evidence base is limited and needs to be expanded. First, the two studies from MAP used measures of neuropathology at autopsy (Boyle et al., 2012; Willroth et al., 2023), which provide an accurate assessment at death but does not capture variation that occurs during life, particularly before the onset of cognitive impairment. Second, there was little variation in the biomarkers in the UK Biobank study (Sutin et al., 2025), which limited the ability to detect an association. Third, larger sample sizes inclusive of a broader spectrum of cognitive health are needed to detect the expected small associations between purpose and the neurobiomarkers.

Purpose in life has been hypothesized to be associated with better cognitive health in older adulthood through clinical, behavioral, and psychological mechanisms (Sutin, Luchetti, Aschwanden, et al., 2023; Sutin et al., 2021). Individuals higher in purpose, for example, are less likely to have diabetes (Hafez et al., 2018), stroke (Kim et al., 2013), or obesity (Fischer et al., 2023), clinical factors implicated in dementia risk, including Alzheimer’s disease as well as vascular dementia (Livingston et al., 2024). In addition, purpose has been associated with more frequent physical activity, measured either with self-report (Kim et al., 2020) or accelerometer (Sutin, Stephan, et al., 2023), and less smoking (Weston et al., 2024). Individuals higher in purpose are likewise less likely to report symptoms of depression (Sutin et al., 2026), which are associated with an increased risk of dementia (Livingston et al., 2024). These factors have been found to account for some, but not all, of the association between purpose in life and dementia risk (Sutin, Luchetti, Aschwanden, et al., 2023). As such, if there is an association between purpose and the neurobiomarkers, it may be due, in part, to these factors.

Regardless of a direct association with any specific neurobiomarker of brain health, purpose in life may be associated with cognitive resilience (Boyle et al., 2012; Willroth et al., 2023). Cognitive resilience refers to the maintenance of cognitive function in the presence of neuropathology and neuronal injury (Stern et al., 2023). That is, some individuals maintain their cognitive function despite the presence of markers of poor brain health that tend to harm cognition (Gómez-Isla & Frosch, 2022). There is great interest in identifying factors that may support cognitive function as long as possible even as the brain declines (Ossenkoppele et al., 2020). The two previous studies in MAP found such evidence for purpose: Participants with greater purpose in life had better cognitive function than would be expected by the amount of neuropathology present at the end of their lives (Boyle et al., 2012; Willroth et al., 2023; the association between purpose and resilience was reported in Willroth and colleagues, in addition to well-being, although the association was not independent of global well-being). Importantly, there does not need to be a direct association between purpose and the neurobiomarkers for it to be associated with greater cognitive resilience.

The present research examines the association between purpose in life and four blood-based neurobiomarkers of ADRD (Aβ42/Aβ40, p-tau181, NfL, GFAP) and cognitive resilience in a large sample of middle-aged and older adults. Based on the literature on purpose and lower risk of ADRD (Boyle et al., 2010; Sutin, Luchetti, Aschwanden, et al., 2023), we hypothesize that higher purpose in life will be associated with higher Aβ42/Aβ40 (indicating lower amyloid burden) and lower p-tau181, NfL, and GFAP. We address generalizability by testing whether these associations are moderated by age, sex, race, ethnicity, education, or genetic risk. The moderation analysis is exploratory. Based on the literature on purpose and cognitive resilience (Boyle et al., 2012; Willroth et al., 2023), we hypothesize that higher purpose in life will be associated with greater cognitive resilience. We test for moderation by the same sociodemographic factors and genetic risk and construe these analyses as exploratory. Across both sets of analyses, we test additional models to examine whether clinical, behavioral, and psychological factors contribute to the association between purpose in life and both the neurobiomarkers and cognitive resilience.

Method

Participants and procedure

Participants were from the Health and Retirement Study (HRS; https://hrs.isr.umich.edu) 2016 Neuro Study. The HRS is a longitudinal study of aging of individuals living in the United States aged 50 and older and their partners, regardless of age. HRS participants are re-interviewed every two years. The 2016 Venous Blood Study (VBS) collected blood from participants (except proxies) who completed the 2016 wave of the HRS and consented to the blood collection (N=9,934). A subsample of the VBS sample was selected for the 2016 Neuro Study. A probability sample of participants who were eligible for the 2016 Harmonized Cognitive Assessment Protocol (HCAP) or who would be eligible for a future HCAP and born in 1959 or earlier was included. A total of 4,539 participants were assayed for the neurobiomarkers (see below). See Faul and colleagues (2025) for detailed information on the protocol and participation rates. The sample that was assayed was similar in racial and ethnic composition as the HRS 2016 core sample.

Since 2006, purpose in life has been measured in the Leave-Behind Questionnaire for half the sample at every assessment. The measurement alternates such that the full sample reports on their purpose every four years. Purpose in life measured in 2016 or the closest previous assessment from 2014 to 2006 was selected for analysis. A total of 4193 participants from the 2016 Neuro Study had reported on their purpose in life. Compared to participants with data on purpose in life (n=4193), participants without data on purpose in life (n=346) were younger (d=−0.78, p<.001), more likely to be male (χ2=9.06, p=.003), more likely to be a race other than white (χ2=132.31, p<.001), more likely to be Hispanic or Latino ethnicity (χ2=96.68, p<.001), and had fewer years of education (d=−.34, p<.001).

The present research was preregistered in July 2024 (https://osf.io/jr7ys). We previously used the HRS data resource to examine the association between purpose in life and risk of dementia (Sutin et al., 2021), cognitive function (Sutin et al., 2022), inflammatory markers (Sutin et al., 2025; Sutin et al., 2023), and how purpose in life changes before and after cognitive impairment (Sutin, Luchetti, Stephan, et al., 2023a). We have not previously accessed or analyzed the biomarkers data from the 2016 Neuro Study.

Prior to accessing the 2016 Neuro Study data in December 2025, we calculated the power needed to detect a significant effect. We took a conservative approach to the expected effect size because previous research on purpose in life and other biomarkers (e.g., inflammation) has indicated a small effect size. As such, we estimated power to detect an effect size of .10 with 90% power from a linear regression model with six independent variables (purpose in life and the five sociodemographic covariates). This power analysis indicated that a sample size of 1749 is needed to detect a significant effect. As such, the sample size of the 2016 Neuro Study is well powered for these analyses.

Measures

Purpose in life.

Purpose in life was measured with a 7-item version of the Purpose in Life scale from the Ryff Scales of Psychological Well-Being (Ryff, 1989). Items (e.g., “I have a sense of direction and purpose in my life”) were rated from 1 (strongly disagree) to 6 (strongly agree). Items were scored in the direction of higher purpose, and the mean was taken across items (possible range 1–6; alpha=.77).

ADRD neurobiomarkers.

The Single Molecule Array (Simoa) HD-X instrument (Quanterix Corporation) was used to assess the neurobiomakers from plasma and serum obtained from venous blood. Aβ40, Aβ42, NfL, and GFAP were assessed with the Neurology 4-Plex E assay from plasma. P-tau-181 was assessed with the p-tau-181V2 assay from serum. More detailed information about the assay for each biomarker can be found in Faul and colleagues (2025). As expected, each biomarker had a skewness >2. Raw values were natural log transformed to normalize the distribution for each marker.

Cognitive function.

Cognitive function was measured with several tasks (https://hrs.isr.umich.edu/sites/default/files/biblio/dr-006_0.pdf). The modified Telephone Interview for Cognitive Status (TICSm) was administered as a common, well-validated measure of cognitive status (Crimmins et al., 2011). The TICSm included three cognitive tasks administered by interviewers: immediate and delayed recall of 10 words (possible range 0–20), serial 7s (subtracting 7 from 100 five times; possible range 0–5), and backward counting (counting backwards from 20 as fast as possible; participants were given a second trial if not completed correctly on the first trial; scored as 0=incorrect both trials, 1=correct on second trial, 2=correct on first trial). Recall measured episodic memory, serial 7s measured working memory, and backward counting measured attention. The total score was the sum of performance on these three tasks (possible range 0–27). An animal naming task was administered where participants had to name as many unique animals as possible in 60 seconds. This task is a measure of verbal fluency. A naming task was administered to assess orientation. The task included eight items that covered dates (current month, day, year, day of week), objects (scissors, cactus), and current President and Vice President. Correct answers were summed into a total score. Numeric reasoning was measured with a number series task where participants had to fill in a missing digit in a series of numbers. The task was scored using the standard algorithm for HRS (see https://hrs.isr.umich.edu/sites/default/files/biblio/dr-027b_0.pdf). An overall cognitive function score was derived by first standardizing the four cognitive measures and then taking the mean of the four measures in the direction of greater cognitive function.

Covariates.

Sociodemographic covariates were age at the assessment of purpose in years, sex (male=0, female=1), race (two dummy-coded variables that compared Black=1 and otherwise identified=1 to white=0), ethnicity (Hispanic/Latino=1, not Hispanic/Latino=0), and education in years. Supplemental analyses controlled for genetic risk, measured as the presence of at least one copy of the APOE e4 risk allele, and some analyses controlled for kidney function, measured as glomerular filtration rate (eGFR)-creatinine estimated based on CKD-EPI criteria. Clinical covariates were reported doctor diagnosis of hypertension, diabetes, or stroke (each coded yes=1, no=0). Body mass index (BMI) was derived from self-reported weight and height and coded as met the threshold (BMI≥30=1) or did not meet the threshold (BMI<30=0) for obesity. Physical activity was the mean of two items on the frequency of engagement in moderate to vigorous activities reported on a scale from 1=more than once a week to 4=hardly ever or never and reverse scored in the direction of greater physical activity. Smoking status was coded as current smokers=1 versus never/former smokers=0. Depression measured with an 8-item (yes/no) version of the Center for Epidemiological Study depression scale and dichotomized at the threshold for severe symptoms (score ≥3=1, score<3=0). Five Factor Model personality traits were measured with the Midlife Development Inventory (Lachman & Weaver, 1997). The clinical, behavioral, and psychological covariates were concurrent with the purpose assessment. All analyses controlled for years between the measurement of purpose in life and the venous blood collection (range 0=2016 to −10=2006).

Statistical Approach

Correlation was used to examine the bivariate association between purpose in life and the four neurobiomarkers and cognitive resilience. Linear regression was used to examine the association between purpose and each neurobiomarker controlling for sociodemographic factors and years to the purpose assessment. Moderation by age, sex, race, ethnicity, education, genetic risk, and year of purpose assessment was tested with an interaction term between purpose in life and each of these factors. Both the main effects and all sociodemographic factors and year of personality assessment were included as covariates. The potential clinical, behavioral, and psychological factors were then added to the model. Supplemental analyses tested whether genetic risk, eGFR, or personality traits accounted for the associations.

Following the same approach as Willroth and colleagues (2023), cognitive resilience was computed as a residual score. Specifically, the four neurobiomarkers were regressed on the overall cognitive score. The residual was saved and used as an index of cognitive resilience such that positive values indicated better cognitive performance relative to the amount of burden detected with the neurobiomarkers, whereas negative values indicated worse cognitive performance relative to the amount of neuropathology detected with the neurobiomarkers. The same set of analyses was run for cognitive resilience as the neurobiomarkers to test for an association between purpose in life and cognitive resilience, whether the association was moderated by sociodemographic factors or genetic risk, and whether the association could be accounted for by genetic risk or clinical, behavioral, and psychological factors. In addition, because of criticism of the residual approach (Elman et al., 2022), resilience was also defined as the interaction between purpose and an overall index of pathology (scored as the mean across the four biomarkers [Aβ42/Aβ40 was multiplied by −1 so that it would be in the same direction as the other three neurobiomarkers]) as predictor of cognitive performance (Elman et al., 2022; Stern et al., 2023).

All participants were included in the main analyses. Supplemental analyses excluded participants with evidence of cognitive impairment at the time of blood collection (TICSm<12; Crimmins et al., 2011) and tested whether the associations were moderated by cognitive status.

Results

Descriptive statistics for all study variables are in Table 1. The association between purpose in life and the four neurobiomarkers is in Table 2. The unadjusted correlations were generally as expected: Higher purpose in life was associated with lower NfL, GFAP, and p-tau181; it was unrelated to the Aβ42/Aβ40 ratio. The association between higher purpose in life and lower NfL was apparent controlling for the sociodemographic factors and years to purpose assessment, whereas the associations with GFAP and p-tau181 were reduced to non-significance. None of the interactions between purpose and the sociodemographic factors was significant, which indicated that the association between purpose in life and each neurobiomarker was not moderated by age, sex, race, ethnicity, or education; year of purpose assessment also did not moderate any association (Supplemental Table S1). The association between purpose in life and NfL was reduced by 50% but persisted (β=−.03, p=.007) controlling for potential mechanisms of the association (obesity, hypertension, diabetes, stroke, physical activity, smoking, depressive symptoms). The associations with the other three biomarkers remained non-significant (Table 2). The association between purpose and NfL remained significant controlling for genetic risk (β=−.06, p<.001), eGFR (β=−.05, p<.001), or personality (β=−.04, p<.001).

Table 1.

Descriptive Statistics for All Study Variables

Variable Mean (SD) or % (n)
Age (years) 68.87 (10.17)
Sex (female) 60.0% (2516)
Race (Black) 26.0% (672)
Race (Otherwise identified) 8.1% (338)
Ethnicity (Hispanic/Latino) 13.4% (561)
Education (years) 12.91 (3.12)
Purpose in life1 4.58 (.93)
Neurobiomarkers (untransformed)
 Aβ42/Aβ40 (n=4124) .07 (2.30)
 p-tau181 (n=4097) 2.11 (2.30)
 Neurofilament light (n=4125) 24.28 (24.77)
 Glial fibrillary acidic protein (n=4125) 105.32 (75.36)
Cognitive function .03 (.98)
Cognitive impairment (yes) 19.8% (830)
Resilience (n=4094) .03 (.77)
Clinical and behavior factors
 Hypertension (yes) (n=4192) 61.5% (2580)
 Diabetes (yes) (n=4191) 25.3% (1061)
 Stroke (yes) 6.9% (291)
 Obesity (yes) (n=4153) 37.6% (1560)
 Physical activity 2.53 (1.06)
 Smoking (n=4192) 12.6% (529)
 Depression (n=4184) 20.5% (858)
APOE (presence of e4 allele) (n=3787) 25.5% (965)
Estimated glomerular filtration rate 78.66 (20.11)
Neuroticism (n=4157) 1.98 (.62)
Extraversion (n=4162) 3.19 (.58)
Openness (n=4146) 2.92 (.57)
Agreeableness (n=5159) 3.51 (.51)
Conscientiousness (n=4160) 3.26 (.50)
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Note. N=4193 unless otherwise specified. SD=standard deviation.

1

The closest assessment of purpose in life to the neurobiomarkers was used for analysis: 46.6% (n=2114) from 2016; 43.3% (n=1967) from 2014, 5.2% (n=237) from 2012, 3.2% (n=143) from 2010, .9% (n=43) from 2008, and .8% (n=35) from 2006.

Table 2.

The association between Purpose in Life and the Four Neurobiomarkers and Resilience (Residual Approach)

Predictor Aβ42/Aβ40 p-tau181 NfL GFAP Resilience
r/β p r/β p r/β p r/β p r/β p
Unadjusted (correlation)
Purpose in life .02 .236 −.03 .038 −.12 <.001 −.04 .005 .19 <.001
Sociodemographic Adjusted (linear regression)
Purpose in life .02 .354 .00 .878 −.06 <.001 .00 .838 .12 <.001
Age −.04 .009 .43 <.001 .66 <.001 .67 <.001 −.10 <.001
Sex (female) −.01 .411 −.16 <.001 .01 .483 .16 <.001 .04 .003
Race (Black) .04 .006 .00 .904 −.03 .033 .04 <.001 −.24 <.001
Race (Otherwise identified) .01 .526 −.01 .707 −.01 .616 .02 .057 −.08 <.001
Hispanic/Latino ethnicity .03 .165 −.04 .018 −.02 .292 −.01 .316 −.10 <.001
Education −.01 .689 .00 .929 −.03 .016 .03 .035 .41 <.001
Year of purpose assessment .04 .025 −.09 <.001 −.16 <.001 −.12 <.001 .05 <.001
Further Adjusted (linear regression)
Purpose in life .00 .934 .01 .420 −.03 .007 .00 .829 .08 <.001
Age −.05 .005 .41 <.001 .61 <.001 .62 <.001 −.12 <.001
Sex (female) −.01 .582 −.16 <.001 .01 .267 .16 <.001 .05 <.001
Race (Black) .05 .002 −.01 .400 −.06 <.001 .05 <.001 −.23 <.001
Race (Otherwise identified) .01 .542 −.01 .415 −.02 .165 .02 .139 −.08 <.001
Hispanic/Latino ethnicity .02 .225 −.04 .008 −.02 .195 −.02 .150 −.10 .017
Education −.02 .330 .00 .962 −.02 .211 .02 .237 .39 <.001
Year .04 .018 −.09 <.001 −.16 <.001 −.12 <.001 .05 <.001
Obesity −.03 .045 −.01 .498 −.11 <.001 −.12 <.001 .01 .402
Hypertension .02 .367 .03 .027 .09 <.001 .04 .004 .01 .315
Diabetes −.04 .022 .05 <.001 .10 <.001 −.01 .490 −.01 .384
Stroke .01 .607 .02 .075 .05 <.001 .03 .005 −.04 .006
Physical activity .06 .001 −.02 .276 −.06 <.001 −.03 .027 .05 <.001
Smoking −.02 .284 −.01 .097 .01 .402 −.08 <.001 −.07 <.001
Depression .00 .929 .01 .379 .00 .939 .01 .635 −.07 <.001
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Note. Ns range from 4,043 to 4125 because of missing data. NfL=neurofilament light (NfL). GFAP= glial fibrillary acidic protein. Significant associations for purpose in life are bolded.

Purpose in life was associated with greater cognitive resilience when measured with the residual approach: Participants higher in purpose in life had better cognitive performance relative to their amount of neurobiological burden (Table 2). This association was apparent across unadjusted, sociodemographic adjusted, and fully adjusted models. It also persisted controlling for genetic risk (β=.12, p<.001), eGFR (β=.12, p<.001), or personality (β=.09, p<.001). The relation was not moderated by age, sex, race, education, genetic risk, cognitive impairment, or year of purpose assessment (Supplemental Table S1). There was an interaction with ethnicity (βinteraction=−.04, p=.003), which, when split by ethnicity suggested a weaker association for Hispanic/Latino participants (β=.08, p=.053) than non-Hispanic/Latino participants (β=.13, p<.001). The association between purpose and resilience did not replicate with the interaction approach to resilience: The interaction between purpose and the index of neurological burden on cognitive performance was not significant (βinteraction=.01, p=.291).

Finally, the association between purpose and the four neurobiomarkers was similar when participants with any cognitive impairment (n=830) were excluded from the sample (Aβ42/Aβ40 ratio: β=.02, p=.191; p-tau181: β=.00, p=.843; NfL: β=−.07, p<.001; GFAP: β=.01, p=.651; resilience: β=.07, p<.001). None of the interactions between purpose in life and impairment status was significant for the four neurobiomarkers or resilience (βinteraction range −.01 to .02, all ns; Supplemental Table S1).

Discussion

The present research found no evidence that purpose in life is associated with neurobiomarkers of Alzheimer’s disease measured from blood: It was unrelated to two markers of the common signatures of the disease, the Aβ42/Aβ40 ratio and p-tau181. Purpose in life did, however, have a robust association with one non-specific marker of brain health, NfL: Higher purpose was associated with lower circulating NfL, an association that was similar across sociodemographic characteristics and persisted controlling for shared risk factors. Purpose was unrelated to GFAP, another non-specific marker of brain health. Finally, evidence that purpose was related to cognitive resilience was mixed. It was associated with more resilience when tested with the residual approach but not with the interaction approach.

Of the four neurobiomarkers of brain health, purpose in life was only associated with less NfL. NfL is a protein specific to neurons that enters the bloodstream when neurons are damaged or die (Gaetani et al., 2019). NfL detected in blood thus reflects neuronal injury, with greater amounts of the protein indicating more damage. It is elevated in numerous neurodegenerative diseases, including amyotrophic lateral sclerosis, multiple sclerosis, and Huntington’s disease, as well as Alzheimer’s disease and other forms of dementia (Gaetani et al., 2019; Mullard, 2023). The Food and Drug Administration has approved it as surrogate marker of neurodegeneration that can be used as an end point when evaluating drugs to treat neurodegenerative diseases (Mullard, 2023). It is also elevated with inflammation, traumatic brain injury, and vascular injury (Khalil et al., 2024). As such, it is a broad measure of the health of the brain rather than a marker of a specific neurological injury or disorder.

The association between purpose in life and lower NfL suggests that individuals higher in purpose may have less neuronal injury. This association may be due, in part, to the overall better brain health of individuals higher in purpose. Purpose in life, for example, is associated with healthier profiles, particularly greater engagement in physical activity (Kim et al., 2020; Sutin, Stephan, et al., 2023), which in turn is associated with less NfL (Hooper et al., 2025). Individuals higher in purpose are also less likely to experience injury to the brain, such as stroke (Kim et al., 2013), which increases NfL (Khalil et al., 2024). The present research suggested that factors such as physical activity and stroke may account for part of the association with NfL, and thus may be mechanisms in this association. NfL could subsequently be one mechanism in the association between purpose and lower risk of developing neurological diseases, including dementia and Parkinson’s disease.

Based on the published literature that relied on neuropathology at autopsy (Boyle et al., 2012; Willroth et al., 2023) and one small study that used the same blood-based neurobiomarkers as the current study (Sutin et al., 2025), it should not be a surprise that purpose in life was unrelated to the neural signatures of Alzheimer’s disease. Still, given both the limitations of these previous studies (e.g., autopsies only measure the final neuropathology at death, the lack of variation in the UK Biobank, small sample sizes that limit statistical power) and that purpose in life is associated with lower risk of Alzheimer’s disease (Boyle et al., 2010; Sutin, Luchetti, Aschwanden, et al., 2023), it was possible that purpose would be associated with Aβ42/Aβ40 ratio and p-tau181. The null associations in a larger sample with more variability in both the biomarkers and cognitive function provide stronger evidence the purpose is not related to amyloid and tau, at least as measured by the Aβ42/Aβ40 ratio and p-tau181.

Purpose in life was also unrelated to GFAP. GFAP is one marker of neuroinflammation that, like NfL, is generally considered as a global marker of brain health that is not specific to one condition or disease (Abdelhak et al., 2022). Purpose in life has been associated consistently with healthier inflammatory profiles, such as lower c-reactive protein (Sutin et al., 2025) and interleukin-6 (Sutin et al., 2023), two common markers of systemic inflammation, as well as lower allostatic load (Lewis & Hill, 2023), another broad measure that reflects inflammatory health. Based on this literature, it was expected that purpose may also be associated with less neuroinflammation, especially in a sample that was varied in terms of cognitive and physical health. The modest bivariate association between purpose and GFAP, however, was reduced to non-significance after adjustment for sociodemographic factors.

There was no evidence that the association between purpose in life and the four neurobiomarkers were moderated by age, sex, race, ethnicity, or education. For NfL, this lack of moderation indicates that the negative association was apparent across these sociodemographic groups. For the other three markers, it indicates that the null association did not vary by these factors, which could have been possible if the association went in opposite directions for specific groups (e.g., relatively older versus relatively younger participants). The associations were also similar when the sample was limited to the cognitively healthy participants, which indicates that the pattern of associations was not driven by the cognitive health of the participants.

It is possible to live with neurodegeneration and not show clinical signs of it. That is, some older adults do not have cognitive impairment despite the presence of neuropathological hallmarks of Alzheimer’s disease (plaques and tangles) at autopsy (Gómez-Isla & Frosch, 2022). As such, not everyone who has the underlying neuropathology will have the clinical symptoms of Alzheimer’s disease. This resilience to AD neuropathology has led to great interest in identifying factors that may promote better outcomes despite the neuropathology. Individuals higher in conscientiousness and lower in neuroticism, for example, are less likely to have been diagnosed with Alzheimer’s disease in life despite significant neuropathology indicative of the disease found at autopsy (Terracciano et al., 2013). Using a residual approach, well-being, including purpose in life, has been associated with better cognitive performance despite the level of neuropathology found at autopsy (Boyle et al., 2012; Willroth et al., 2023). The availability of blood-based biomarkers enables this question to be addressed prior to mortality. That is, neurological burden can be assessed with biomarkers that can be assayed from a standard blood draw. The present research is consistent with the findings based on autopsy: Participants with more purpose had better cognitive function relative to their neuropathological burden. This association was apparent across sociodemographic groups but varied in strength by ethnicity: The association between purpose and cognitive resilience was stronger among non-Hispanic/Latino individuals than Hispanic/Latino individuals. This pattern suggests that individuals from this population may not benefit as much from having higher purpose in life in the context of cognitive resilience.

The residual approach to testing resilience, however, has been criticized because the residualized score is correlated with the outcome (i.e., cognition). Elman and colleagues (2022) argue that an association between a predictor and cognitive resilience depends on the initial association between the predictor and cognitive function. As such, there may be an association between purpose and resilience because of the correlation between purpose and cognition. And, in fact, the correlation between purpose and cognitive function in the current sample was .21. Elman and colleagues recommend testing resilience with an interaction approach. A significant interaction that would demonstrate resilience would be if purpose was associated with better cognitive performance as the degree of neuroburden increased. In the present analysis, this interaction was not significant and thus did not support the argument for purpose as a resilience factor. It is worth noting, however, that interactions are difficult to detect and difficult to replicate (Sherman & Pashler, 2019). An interaction approach may thus also have its challenges, too. Longitudinal data that can be used to predict changes in cognitive status are needed to test whether purpose is protective against the development of cognitive impairment among individuals with neurological burden but healthy cognitive function at baseline.

There are also limitations to these specific blood markers, particularly the Aβ42/Aβ40 ratio and p-tau181 measured with the Quanterix assay. The ability to test for markers of ATN in blood opens up new and powerful directions for research on neuropathology across the continuum of the disease, particularly before cognitive impairment in large, population-based samples with stored blood. At the same time, the Quanterix SIMOA Aβ assays in particular have been found to have relatively low accuracy in predicting amyloid PET and CSF (Brand et al., 2022; Janelidze et al., 2021). In this sample, there were weak or null associations between the Aβ42/Aβ40 ratio even with age, education, and cognition. As such, the association with Aβ42/Aβ40 ratio and p-tau181 may be limited by the reliability of how these markers are measured. There continues to be great strides in the development of assays to measure neurobiomarkers of cognitive health from blood. Since the association is likely to be modest, more reliable measures may be better able to detect the signal with purpose in life.

The present study had several strengths, including the novel biomarkers, relatively large sample size, and cognitive range of the sample. There are also limitations. As just described, there are limitations to the Aβ42/Aβ40 ratio and p-tau181 assays as measures of amyloid and tau burden, respectively. Future research could use p-tau217 to better identify neuropathology specifically related to Alzheimer’s disease. In addition, there was just one assessment of the biomarkers. It would be useful in future research to have longitudinal biomarker assessments to test whether purpose is associated with resistance to neuropathology (i.e., less accumulation of neuropathology over time; Ourry et al., 2024) and to examine potential bi-directional associations over time (i.e., greater neurodegeneration may be associated with declines in purpose). Future research could also test other potential mechanisms, such as stress reactivity given that higher purpose tends to be associated with dampened physiologic arousal/reactivity during stressful tasks (Fogelman & Canli, 2015). There was also a time gap for some participants between their purpose assessment and the biomarkers, although this gap did not moderate any of the associations. Still, future research could have the neurobiomarkers concurrent with the assessment of purpose. Finally, the current results are based on a single sample from a high-income country. A wider variety of samples in needed, particularly samples from lower- and middle-income countries, to better evaluate generalizability.

The present research indicates that purpose is associated with less neuronal injury, as measured with a general marker of neuronal health that is consistent with the broad, healthier cognitive correlates of purpose in life. The present findings also suggest an association with resilience based on the residual method. Future research is needed to better address both resilience and other neuropathological measures of brain health that could be mechanisms between purpose and lower risk of neurodegenerative diseases.

Supplementary Material

1

Acknowledgments:

We gratefully acknowledge the parent studies whose public data made this work possible: The Health and Retirement Study is sponsored by the National Institute on Aging (NIA-U01AG009740) and conducted by the University of Michigan.

Funding:

This work was supported by the National Institute on Aging of the National Institutes of Health under Award Number R01AG074573. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The funder had no role in study design, analysis, interpretation, preparation of the manuscript for publication, or the decision to publish.

Footnotes

Conflict of Interest: None

Preregistration: This research was preregistered: https://osf.io/jr7ys.

Data Availability:

Data are available to the public from the Health and Retirement Study at https://hrs.isr.umich.edu

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

1
NIHMS2185671-supplement-1.pdf (227.6KB, pdf)

Data Availability Statement

Data are available to the public from the Health and Retirement Study at https://hrs.isr.umich.edu

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