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Stage 1 IPA at PCI RR

This pre-registration is part of a larger replication effort of the influential study by Lally et al. (2010) ​​in which they tracked the subjective automaticity of a novel, daily (eating or exercise-related) routine, using the Self-Report Habit Index across 12 consecutive weeks. The replication of the main finding (that it takes 66 days to form a new habit) has been addressed in a separate pre-registration (https://osf.io/bj9r2). In the current extension of this basic replication, we will investigate potential causes of interindividual variability, including the consistency and complexity of the habit, as well as individual differences in impulsivity, personal need for structure (PNS), conscientiousness, effort, intention, and reward. Consistency and complexity were already explored by Lally et al., but they could not draw strong conclusions due to their small sample size. Individual differences in impulsivity, PNS, and conscientiousness were not included in the original publication, but they were part of the original study protocol. In addition to addressing the research questions of the original study, we will also investigate how anticipated effort, intention, and reward influence habit formation.

A previous clinical trial including patients with a BMI between 30 and 40 kg/m² has shown that using the digital treatment programme zanadio for the duration of 12 months led to a clinically relevant and significant weight loss in the intervention group (IG), which was significantly higher than in the care-as-usual control group (CG). Secondary endpoints, i.e., quality of life, well-being and the waist-to-height ratio improved significantly in the IG during the 12 month study period. Compared to the first clinical trial to evaluate zanadio, in which only participants with BMI grade I and II were allowed, the present study also includes participants with BMI grade III, in order to evaluate the effectiveness of zanadio across different BMI grades and in particular for patients with BMI grade III. The primary endpoint is the percentage weight change compared to baseline. The secondary endpoints are well-being, waist-to-height ratio and obesity-specific quality-of-life. Moreover, changes in mal-adaptive eating behaviours, i.e., emotional, restraint and external eating, that might influence weight and weight maintenance, will be analysed. Data of the primary and secondary endpoints are collected via telephone interviews and online surveys at baseline and every 3 months for 12 months (T0-T4). In this study we specifically included a pertinent proportion of male patients, who were sparsely represented in the previous clinical trial (Roth et al., submitted) and who are generally less likely to participate in behavioural obesity treatment programmes (Jebb et al., 2011; Sepah et al., 2017). By doing so, gender-specific differences can be exploratively evaluated.

Obesity may be associated with differences in central dopamine levels, a neurotransmitter important for motivation, cognitive control and decision making (Horstmann, Fenske, & Hankir, 2015). Such differences in the dopaminergic system might explain impaired cognitive processes like reinforcement learning and working memory found in obese compared to normal weight people (Horstmann, 2017; Mathar, Neumann, Villringer, & Horstmann, 2017; Yang, Shields, Guo, & Liu, 2018). However, recent research results from animal studies suggest that not only obesity itself contributes to such changes, but that the consumption of saturated fat and refined sugar (HFS) can independently lead to alterations in the dopaminergic system. Interventional studies in rodents have provided evidence for altered dopaminergic transmission, e.g. downregulated dopamine receptor expression (Adams et al., 2015; Hakim & Keay, 2019), decreased dopamine release (Barnes, Wallace, Jacobowitz, & Fordahl, 2020; Patel et al., 2018), and reduced dopamine clearance (Cone, Chartoff, Potter, Ebner, & Roitman, 2013) after short- or long-term exposure to HFS. Such changes in the dopaminergic system might influence cognitive processes and behavior in humans. In fact, correlational observations provide first evidence for a link between HFS and general cognition. Higher intake of saturated fat and sugar was associated with poorer global cognition (Zhang, Mckeown, Muldoon, & Tang, 2006), cognitive decline (Okereke et al., 2012) or poorer memory (Attuquayefio et al., 2016). The impact of HFS on specifically the human dopaminergic system and possible behavioral effects have not been investigated so far. Our first study, investigating the link between HFS and the dopaminergic system in humans revealed that HFS consumption was associated with elevated peripheral dopamine precursor (pDAP) availability and altered effects of a dietary dopamine depletion on working memory (Hartmann et al., 2019). Availability of pDAP can be regarded as proxy for striatal dopamine levels (Leyton et al., 2004; Montgomery, McTavish, Cowen, & Grasby, 2003), hinting at first evidence for possible HFS-associated differences of the dopaminergic system in humans. Efficient cognitive control, the ability to exert goal-directed choices, is substantial in everyday life. Maintaining mental representations of goal-relevant stimuli in working memory and being able to update these representations when necessary, but also securing them by ignoring irrelevant stimuli is essential for guiding goal-directed choices. Frontostriatal loops have been implicated in governing these types of working memory processes. Flexibly updating task-relevant information has been shown to involve the dorsal striatum (Fallon & Cools, 2014; Fallon, van der Schaaf, ter Huurne, & Cools, 2017), whereas stable maintenance of representations and ignoring irrelevant information seems to rely on the prefrontal cortex (PFC; (Curtis & D’Esposito, 2003; Fallon et al., 2017). Both brain regions receive dopaminergic input from the midbrain; the dorsal striatum is innervated by dopaminergic neurons from the substantia nigra via the nigrostriatal pathway (Prensa, Giménez-Amaya, Parent, Bernácer, & Cebrián, 2009) and the PFC receives dopaminergic signaling from the ventral tegmental area (Westerink, Enrico, Feimann, & De Vries, 1998). Neurocomputational models suggest that D1 and D2 receptor activation in the striatum and the PFC modulate the ability to update or ignore distracting stimuli (Durstewitz & Seamans, 2008; Hazy, Frank, & O’Reilly, 2007; O’Reilly & Frank, 2006). One of our main hypotheses is that, due to changes within the dopaminergic system, HFS consumption is associated with altered working memory updating and ignoring in a delayed match-to-sample task with distractors (adapted from Fallon & Cools, 2014; Fallon et al., 2017). Striatal and prefrontal dopamine transmission, determined by e.g. dopamine levels and dopamine receptor availability, are also depending on genetic variability, which determines the baseline of the dopaminergic system. Among many single nucleotide polymorphisms (SNPs) known to play a role within the dopaminergic system, the Val158Met polymorphism of the catechol-O methyltransferase (COMT) and the Taq1A polymorphism within the ANKK1 gene are fairly well studied, especially in the context of working memory stability/flexibility. Carrying the Val allele of the COMT Val158Met polymorphism results in higher COMT activity and subsequently lower synaptic dopamine levels (Chen et al., 2004). The effect of this polymorphism is supposedly most prominent in the prefrontal areas where dopamine active transporters are sparse (Sesack, Hawrylak, Matus, Guido, & Levey, 1998) and has been related to executive function and working memory in humans (S. J. Fallon, Williams-Gray, Barker, Owen, & Hampshire, 2013; Joober et al., 2002; Xu et al., 2007). Though not directly coding for a protein within the dopaminergic system, the Taq1A polymorphism affects dopamine D2 receptor (DRD2) density in the striatum (Jönsson et al., 1999; Pohjalainen et al., 1998) and is supposed to modulate working memory vicariously (Nymberg et al., 2014). Combined, the COMT and Taq1A polymorphisms seem to influence general working memory and specifically updating of working memory in an interactive manner (Berryhill, Wiener, Stephens, Lohoff, & Coslett, 2013; Garcia-Garcia, Barceló, Clemente, & Escera, 2011; Stelzel, Basten, Montag, Reuter, & Fiebach, 2009). Reuter and colleagues proposed a COMT-DRD2 Equilibrium model where COMT and Taq1A genotype combinations suggesting a balance between prefrontal dopamine and striatal DRD2 density perform differently on tasks of working memory than unbalanced genotype combinations (Garcia-Garcia et al., 2011; Reuter, Schmitz, Corr, & Hennig, 2006; Reuter et al., 2005) We hypothesize that the COMT Val158Met and the Taq1A polymorphism will interact with dietary style (low vs. high fat and sugar) and the presumed associated alterations within the dopaminergic system to modulate working memory updating and ignoring.

This preregistration gives an overview of the background, overarching hypotheses, and design of a large study consisting of several subprojects. Detailed information about the subprojects and the respective analysis plans can be found in separate preregistrations.