Age Differences in Cortical Thickness and their Association with Cognition in Chimpanzee (Pan troglodytes)

One remarkable feature of humans is our lifespan; humans can live more than 100 years compared to approximately 50 to 60 years in one of our closet living relatives, the chimpanzee (Bronikowski et al., 2011). The duration of the post-reproductive lifespan is particularly significant, as humans can live more than 30 years beyond the period of their reproductive cessation compared to other nonhuman primates (Alvarez, 2000; Hawkes, 2003; Hawkes and Coxworth, 2013; Herndon, 2009), including chimpanzees which is estimated to be a maximum of 5 years (Havercamp et al., 2019; Judge and Carey, 2000; Levitis et al., 2013). In short, humans have remarkable potential longevity during the post-reproductive phase of life which may contribute to our species’ vulnerability to a variety of maladies associated with increasing age, notably neurodegenerative disorders including Alzheimer's disease (AD) and related forms of dementia (Finch, 2010; Walker and Jucker, 2017).

Many studies have examined age-related changes in cognition in nonhuman primates with aged individuals generally performing significantly worse on measures of learning and memory compared to younger adult individuals (Herndon et al., 1997; Joly et al., 2014; King and Michels, 1989; LaClair and Lacreuse, 2016; Lacreuse et al., 1999; Moss et al., 1988; Munger et al., 2017; Nagahara et al., 2010; Picq, 2007; Rapp and Amaral, 1989, 1992; Workman et al., 2019). Similarly, a number of investigations of postmortem brains have described neuropathological and structural changes in the brains of aged nonhuman primates compared to those of younger individuals (Elfenbein et al., 2007; Frye et al., 2020; Hara et al., 2012; Heuer et al., 2017; Rosen et al., 2011; Schultz et al., 2000; Uno and Walker, 1993). Similarly, investigators have used in vivo neuroimaging to document age-related changes in whole brain gray and white matter volume, gyrification and cortical thickness in monkeys (Alexander et al., 2008; Chen et al., 2013; Koo et al., 2012; Matochik et al., 2000).

One group of nonhuman primates that has received considerably less attention in studies on the comparative biology of aging are great apes (chimpanzees, bonobo, gorillas and orang-utans). Besides their greater genetic similarity to humans compared to other nonhuman primate species, recent studies have documented cross-sectional and longitudinal changes in cognition and motor skill in chimpanzees (Hopkins et al., 2021a; Hopkins et al., 2015; Lacreuse et al., 2018; Lacreuse et al., 2014; Manrique and Call, 2015). Studies also have demonstrated the co-occurrence of both neurofibrillary tangles (NFT) and amyloid-beta plaques (Aβ) in elderly chimpanzee postmortem brains (Cramer et al., 2018; Edler et al., 2017; Gearing et al., 1994; Perez et al., 2013; Rosen et al., 2008). The presence of both Aβ plaques and NFT is used to definitively confirm a diagnosis of AD in humans. Though other aged nonhuman primate species develop either Aβ or NFTs, not many are jointly expressed in postmortem brains to the extent seen in chimpanzees. One important distinction between humans and chimpanzees is the absence of overt neuron loss that typically accompanies AD pathology in humans, which suggests that these lesions are not as toxic to the chimpanzee brain. Though important differences exist between humans and chimpanzees in regards to neuropathology and the brain's astrocyte and microglial activation in response (Edler et al., 2020), chimpanzees appear to be the only known species to naturally develop a homolog to human-like AD pathology, and further studies of the similarities and differences in aged primates could lead to important findings that will help improve the efficacy of therapeutic AD models (Edler et al., 2018; Munger et al., 2018; Rosen et al., 2016).

Previous reports in chimpanzees have also identified small to moderate age-related changes in total brain volume, frontal lobe volume, white matter volume, gray matter cortical gyri and sulci thickness (Autrey et al., 2014; Chen et al., 2013; Herndon et al., 1999; Sherwood et al., 2011). Moreover, two recent reports demonstrated age-related loss in gray matter volume in elderly chimpanzees compared to middle-aged and younger individuals using voxel-based morphometry (Lacreuse et al., 2020; Vickery et al., 2020); however, to date, only a single study reported age-related changes in cortical thickness (CT) in chimpanzees. Specifically, Hopkins et al. (2019) reported that whole brain CT was negatively associated with increasing age. One limitation of the Hopkins et al. (2019) paper was the inclusion of only a few old apes (only 7 individuals over 40 years of age), and the analyses focused on whole brain rather than region-specific changes in CT with age. Here, we sought to expand on these previous findings in chimpanzees in two ways. First, we sought to examine age-related changes of CT in a larger cohort of chimpanzees with a greater number of elderly individuals . Specifically, in this study, measures of CT were obtained in an additional 138 chimpanzees and when combined with the data from Hopkins et al. (2019) resulted in a total sample of 225 subjects. Further, within the new cohort of 138 chimpanzees, there were 28 chimpanzees over the age of 40 years which was a three-fold increase in elderly chimpanzees with the total sample. Second, the previous study by Hopkins et al. (2019) focused only on whole brain measures of cortical thickness. In this study, we expanded the analyses to allow for testing of region-specific differences in CT among age groups after adjustment for whole brain cortical thickness. Based on previous studies in human and nonhuman primates, we hypothesized that older chimpanzees would show smaller CT than middle-aged and young chimpanzees.

We also tested for age group differences in CT asymmetries in the chimpanzee sample. In humans, it has been hypothesized that increasing age is associated with changes in functional and anatomical asymmetries, particularly in brain regions that play a role in cognitive and motor functions that decline in elderly populations (Dolcos et al., 2002; Donix et al., 2013; Kong et al., 2018; Roe et al., 2020; Roe et al., 2021). Whether nonhuman primates show age-related differences in CT asymmetries or any other measures of lateralization remains largely unknown and untested (Marie et al., 2018; Rogers, 2021; Spocter et al., 2020). Indeed, we know of no studies that have reported age-related changes in lateralization in cerebral structure or function in nonhuman primates, particularly between elderly individuals and adults. Thus, this analysis is the first of its kind in nonhuman primates. To test for age differences in CT, structural MRI scans were obtained in a sample of pedigreed captive chimpanzees, and following previously described methods (Hopkins et al., 2017), we used an automated pipeline program in Freesurfer to extract cortical thickness measures from 34 neocortical regions (see Figure 1). The cortical thickness for each region was then compared among chimpanzees from different age groups. Based on previous studies in human and nonhuman primates, we hypothesized that cortical thickness would differ between aged and younger adult chimpanzees. If asymmetries in CT are associated with aging, then we further hypothesized that significant differences would be found between age groups.

Finally, we tested for associations between CT and individual differences in general cognitive abilities in the chimpanzees. Specifically, in humans, a number of studies have reported significant associations between global and region-specific CT and general intelligence (Bajaj et al., 2018; Habeck et al., 2020; Menary et al., 2013). As noted above, previous studies in chimpanzees reported a quadratic association between age and overall cognitive performance with young and elderly chimpanzees performing more poorly than middle-aged apes (Hopkins et al., 2021a). Here, we measured general cognitive abilities using the Primate Cognition Test Battery (PCTB), a 13-item set of tasks designed to assess social and physical cognition (Herrmann et al., 2007; Herrmann et al., 2010; Hopkins et al., 2014; Lacreuse et al., 2014; Russell et al., 2011). In this study, based on their weighted average performance across all PCTB tasks, chimpanzees were classified as performing above or below average. We then compared cortical thickness measures between these two groups across age groups. We hypothesized that significant differences in CT would be found between chimpanzees based on their task performance, and these differences would be the greatest in the elderly chimpanzees.

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