# Human GLP1R variants affecting GLP1R cell surface expression are associated with impaired glucose control and increased adiposity

Wenwen Gao, Lei Liu, Eunna Huh, Florence Gbahou, Erika Cecon, Masaya Oshima, Ludivine Houzé, Panagiotis Katsonis, Alan Hegron, Zhiran Fan, et al.

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Wenwen Gao, Lei Liu, Eunna Huh, Florence Gbahou, Erika Cecon, et al. Human GLP1R variants affecting GLP1R cell surface expression are associated with impaired glucose control and increased adiposity. Nature Metabolism, 2023, 10.1038/s42255-023-00889-6. hal-04233247

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Submitted on 23 Nov 2023

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1 Human GLP1R variants affecting GLP1R cell surface expression are associated with

2 impaired glucose control and increased adiposity

3 Wenwen Gao<sup>1,2</sup>, Lei Liu<sup>1,3</sup>, Eunna Huh<sup>4</sup>, Florence Gbahou<sup>1</sup>, Erika Cecon<sup>1</sup>, Masaya Oishma<sup>1</sup>,

4 Ludivine Houzé<sup>1</sup>, Panagiotis Katsonis<sup>4</sup>, Alan Hegron<sup>1,5,6</sup>, Zhiran Fan<sup>3</sup>, Guofei Hou<sup>3</sup>, Guillaume

5 Charpentier<sup>7</sup>, Mathilde Boissel<sup>8</sup>, Mehdi Derhourhi<sup>8</sup>, Michel Marre<sup>9,10</sup>, Beverley Balkau<sup>11</sup>,

6 Philippe Froguel<sup>8,12</sup>, Raphael Scharfmann<sup>1</sup>, Olivier Lichtarge<sup>4,13</sup>, Julie Dam<sup>1</sup>, Amélie

7 Bonnefond<sup>8,12,14</sup>, Jianfeng Liu<sup>3,14,*</sup>, Ralf Jockers<sup>1,14,15,*</sup>

8

9 <sup>1</sup> Université Paris Cité, Institut Cochin, INSERM, CNRS, 75014 Paris, France

10 <sup>2</sup> State Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases,

11 Key Laboratory for Zoonosis Research of the Ministry of Education, Institute of Zoonosis, and

12 College of Veterinary Medicine, Jilin University, Changchun 130062, China

13 <sup>3</sup> Cellular Signaling Laboratory, International Research Center for Sensory Biology and

14 Technology of MOST, Key Laboratory of Molecular Biophysics of Ministry of Education,

15 School of Life Science and Technology, Huazhong University of Science and Technology,

16 Wuhan, China

17 <sup>4</sup> Department of Pharmacology and Chemical Biology, Baylor College of Medicine, Houston,

18 TX 77030, United States of America

19 <sup>5</sup> Institute for Research in Immunology and Cancer, University of Montreal, Montreal, QC,

20 Canada

21 <sup>6</sup> Department of biochemistry and Molecular Medicine, University of Montreal, QC, Canada

22 <sup>7</sup> CERITD (Centre d'Étude et de Recherche pour l'Intensification du Traitement du Diabète),

23 Evry, France

24 <sup>8</sup> University of Lille, Inserm UMR1283, CNRS UMR8199, European Genomic Institute for

25 Diabetes (EGID), Institut Pasteur de Lille, Lille University Hospital, Lille, 59000, France

26 <sup>9</sup> Institut Necker-Enfants Malades, INSERM, Université de Paris, Paris, France

27 <sup>10</sup> Clinique Ambroise Paré, Neuilly-sur-Seine, France

28 <sup>11</sup> Inserm U1018, Center for Research in Epidemiology and Population Health, Villejuif, France

29 // University Paris-Saclay, University Paris-Sud, Villejuif, France

30 <sup>12</sup> Department of Metabolism, Imperial College London, London, W12 0NN, United Kingdom

31 <sup>13</sup> Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX

32 77030, United States of America

33 <sup>14</sup> Co-senior authors

34 <sup>15</sup> Lead contact

35 * Correspondence: ralf.jockers@inserm.fr (R.J.), jfliu@mail.hust.edu.cn (J.L.)

36

37 Running title: Functional diversity of GLP1R variants

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## Abstract

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The glucagon-like peptide 1 receptor (GLP1R) is a major drug target with several agonists being prescribed in patients with type 2 diabetes (T2D) and obesity ¹,². The impact of genetic variability of GLP1R on receptor function and its association with metabolic traits are unclear with conflicting reports. Here, we performed a functional profiling of 60 GLP1R variants across four signaling pathways and revealed an unexpected diversity of phenotypes ranging from defective cell surface expression to complete or pathway-specific gain- (GoF) and loss-of-functions (LoF).

The defective insulin secretion of GLP1R LoF variants was rescued by allosteric GLP1R ligands or high concentrations of exendin-4/semaglutide in INS-1 823/3 cells. Genetic association studies in 200K participants from the UK Biobank show that impaired GLP1R cell surface expression contributes to poor glucose control and increased adiposity with increased HbA1c, BMI and diastolic blood pressure. This study defines impaired GLP1R cell surface expression as a risk factor for T2D- and obesity-associated traits and provides potential treatment options for GLP1R LoF variant carriers.

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## MAIN

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While GLP1R³ is a major T2D and obesity drug target, the consequences of GLP1R variants on receptor function and metabolic traits have remained poorly defined¹. Conflicting results have been reported for frequent variants, including GLP1R LOF variants that are not associated with metabolic diseases⁴, ⁵, ⁶ and causality with disease risk was difficult to establish as these variants were in linkage disequilibrium with other genes. Here, we performed large-scale functional genetics of rare GLP1R variants enabling putative causality. Among the 132 GLP1R variants available in the ExAC browser in 2016, we selected 34 rare missense GLP1R variants i. which are predicted to be of moderate to high impact based on their evolutionary action (EA)
scores⁷,⁸, ii. for which literature data was available on the functional consequences of alanine
mutations⁹, iii. which were located in transmembrane and intracellular domains, known to be
important for receptor activation and signal transduction (Fig. 1a, Extended Data Fig. 1a and
Supplementary Table 1). In parallel, we sequenced GLP1R in 8,672 participants from the
RaDiO study¹⁰. Among 46 detected missense variants, we selected 25 rare variants and a
common one encoding p.A316T because of their high predicted functional impact (Fig. 1a,
Extended Data Fig. 1b and Supplementary Table 1). In total, 60 GLP1R variants were selected
for functional analyses (Fig. 1b).

We first determined the abundance of wild-type (WT) and each mutant GLP1R at the cell surface
in HEK293T cells which do not endogenously express GLP1R, and in rat insulinoma INS-1 823/3
(Glp1r KO) cells deleted of its endogenous Glp1r gene¹¹. Transfection of WT GLP1R with a N-
terminal SNAP-flag-tag resulted in expression levels similar to endogenous GLP1R levels found
in mouse pancreatic islets¹² (Extended Data Fig. 2a-d). Similar results were obtained with non-
tagged WT GLP1R (Extended Data Fig. 2e). In HEK293T cells, total expression of 22 mutants
was significantly lower than WT GLP1R (Fig. 1c (color code)). For a subset of mutants,
trafficking to the cell surface was in addition significantly affected resulting in 31 variants with
significantly reduced surface expression (Fig. 1c (size of bubbles) and Supplementary Table 2a).
In INS-1 823/3 (Glp1r KO) cells total and surface expression was detectable for all mutants
except for p.N320Y and p.I400R (Extended Data Fig. 2f and Supplementary Table 2b). Surface
levels matched well in both cell types with occasional deviations for some variants but without
any systematic trend towards higher or lower expression in either cell system (Fig. 1d). Defects
in receptor trafficking and total expression contributed both to impaired surface expression
(Extended Data Fig. 2g,h). Collectively, 22 out of 60 mutants showed significantly reduced cell
surface expression in both INS-1 823/3 (Glp1r KO) and HEK293T cells.
We next established the signaling profile of WT GLP1R and 60 mutants on four signaling pathways (cAMP accumulation, Ca²⁺ mobilization, ERK activation, and β-arrestin 2 (β-arr2) recruitment) in HEK293T cells. No spontaneous receptor activity was observed in the absence of ligand for any pathway for WT GLP1R (Extended Data Fig. 3a-d, f) and the mutants (data not shown). Ex-4 concentration-response curves were generated for the different signaling pathways (Extended Data Fig. 3a-f). To account for differences in cell surface expression levels of GLP1R mutants, we determined the correlation between GLP1R cell surface expression and Emax and EC₅₀ values for Ex-4 at different WT GLP1R expression levels (Extended Data Figs. 4a-c and 5) and we performed experiments with expression-matched WT GLP1R (Extended Data Fig. 4d-g). EC₅₀ values were unaffected by the surface expression (Extended Data Figs. 4c and 5c,f,i) and Emax values correlated positively with surface expression with a saturation observed for the cAMP pathway at 10 ± 3% cell surface expression (Extended Data Figs. 4b and 5b,e,h).

For the cAMP pathway LoF and GoF variants were observed (Fig. 2 and Extended Data Fig. 6 and Supplementary Table 3a). Most LoF mutants can be explained by impaired cell surface expression impacting either EC₅₀ or Emax (Extended Data Fig. 4h-k). Interestingly, p.R380C shows normal surface expression but the most severe loss in Ex-4 affinity of all variants (1.5 logs; IC₅₀=400 nM) (Fig. 2b and Extended Data Fig. 7). GoF mutants show increased Emax values despite normal surface expression. Ca²⁺ mobilization is affected in 2/3 of the studied GLP1R mutants with both LoF and GoF in Emax (Fig. 2 and Extended Data Fig. 6 and Supplementary Table 3b). Twenty-seven mutants showed significantly impaired ERK1/2 activation and one mutant (p.S258L) increased ERK1/2 activation (Fig. 2 and Extended Data Fig. 6 and Supplementary Table 3c). The β-arr2 pathway represents the pathway for which most of the mutants are affected with diminished EC₅₀ and/or Emax (Fig. 2 and Extended Data Fig. 6 and Supplementary Table 3d). GoF was not observed for this pathway. Based on all these functional analyses we grouped the mutants into eight categories: those with severely impaired cell surface
114 expression (less than 10 ± 3 %), those with all four or two or three pathways impaired, those with
115 specific defects only in β-arr2 recruitment or ERK1/2 signaling, those exhibiting a gain-of-
116 function (GoF) in cAMP or Ca²⁺ signaling, and those similar to WT GLP1R (Fig. 2a-h and
117 Extended Data Fig. 6a-h).

118 To further evaluate the overall signaling efficiencies of each mutant, we determined their
119 transduction coefficient log(τ/Kₐ), and compared the values of the WT receptor and each mutant
120 by subtracting the corresponding transduction coefficient and expressed it as Δlog(τ/Kₐ)
121 (Supplementary Table 3a-d). We then plotted radial graphs containing Δlog(τ/Kₐ) together with
122 Emax values for all pathways to generate a visible signaling signature for each mutant (Fig. 3 and
123 Extended Data Fig. 6). When excluding the mutants with severely impaired cell surface
124 expression, the cAMP pathway turned out to be the most affected pathway, with eight mutants
125 displaying Δlog(τ/Kₐ) values of up to -3.16, which is significantly different from zero, the
126 reference value (Supplementary Table 3a), followed by β-arr2 recruitment (Supplementary Table
127 3d) with seven mutants with modest Δlog(τ/Kₐ) values (between -1.00 and -1.54). Only three and
128 zero mutants showed statistically significant Δlog(τ/Kₐ) values for Ca²⁺ mobilization
129 (Supplementary Table 3b) and ERK1/2 activation (Supplementary Table 3c), respectively.

130 Interestingly, some of the variants showed signaling bias. Five variants encoding p.R227C,
131 p.Y291C, p.R310Q, p.I357F and p.E408G (Extended Data Fig. 6) were G protein-biased with
132 loss of β-arr2 recruitment but activation of the Gs/cAMP pathway and the Gq/11/ Ca²⁺ pathway
133 (Supplementary Table 3b). Among these, p.E408G showed even GoF for Ca²⁺ mobilization and
134 p.Y291C for both Ca²⁺ mobilization and cAMP production. None of the mutants were biased
135 towards β-arr2. Three variants encoding p.H173P, p.R190Q (Extended Data Fig. 6) and p.R380C
136 (Fig. 2b) were strictly Gs/cAMP biased, as activation of all other pathways were undetectable.

137 Another remarkable finding of our study was that, for many mutants, GoF or LoF was not a
138 general feature of the mutant but was restricted to specific signaling pathways, leading to
complex and different signaling signatures for each variant. In some cases, GoF and LoF phenotypes were observed for the same mutants, as exemplified by five mutants with LoF for β-arr2 recruitment combined with GoF for Ca²⁺ mobilization (p.E408G, p.W417G), for cAMP production (p.I357F) or for both pathways (p.Y291C, p.A316T) (Extended Data Fig. 6d,g,f, Fig. 2g).

We next performed an unbiased cluster analysis of those mutants for which signaling data were obtained for at least one pathway (56 variants) (Fig. 3). Non-negative matrix factorization (nnmf) and k-means were used to unbiasedly group the variants. To have a unique measure representing the signaling signatures of each variant, we defined the “phenotype score” as the positive-sum average of 12 signaling parameters. The mutants with different signaling profiles fitted best into three distinct clusters (Fig. 3a). Mutants in the first cluster (red, 13 variants) are characterized by complete loss of β-arr2 response and drastically reduced potency of the cAMP response. They also lost mid to high range of efficacy in ERK1/2. In the second cluster (blue, seven variants), β-arr2 responses are detectable, but with drastic losses in Emax and τ/Ka. They also show reduced ERK1/2 efficacy, while increased ERK1/2 potency. Signaling impairments varied in Cluster 3 (black, 36 variants) with the variants with the lowest phenotypic scores belonging to this group (Fig 3a,b). The overlay of the different members of each cluster is shown in Fig 3c.

We then compared the experimentally obtained phenotypic score for those mutations located in the transmembrane region with six different scoring algorithms including EA, REVEL, CADD, SIFT, PolyPhen2, and MutationAssessor (Extended Data Fig. 8). CADD and EA scores showed the best R squares (0.46 and 0.42). The EA score showed the steepest slope (x-coefficient=0.0101), meaning the best discriminatory information, and showed also the lowest number of false positives (mutants with high predicted score (>80) but low phenotypic score) confirming the high value of the EA score in predicting the effect of variants on receptor fitness (Fig. 3d).
Among the GLP1R variants that were functionally analyzed in vitro, 35 variants were present in the 200K exome data of the UK Biobank (Supplementary Table 1). We could therefore assess the association between these GLP1R variants and various metabolic traits in UK Biobank. In the carriers, each GLP1R variant was heterozygous. Using the mixed-effects score test (MiST) method adjusted for relevant covariates, the burden of rare, loss-of-function GLP1R variants impairing cell surface expression was significantly associated with increased glycated hemoglobin A1c (Hb1Ac) (P = 6.9×10⁻⁴ with an effect [β] of 0.95±0.28), increased body mass index (BMI) (P = 2.6×10⁻³ with a β of 0.032±0.011) and increased diastolic blood pressure (P = 0.044 with a β of 1.3±0.62 (Fig. 3e and Extended Data Fig. 9)). These associations were stronger when rare, null (i.e. nonsense, frameshift, canonical ±1 or 2 splice sites, start lost) variants in GLP1R that were detected in the 200K exome data of the UK Biobank (Supplementary Table 4) were also included in the burden of GLP1R variants (P = 2.8×10⁻⁴ with a β of 0.98±0.27, P = 8.7×10⁻⁴ with a β of 0.034±0.010 and P = 0.023 with a β of 1.4±0.60, respectively) (Fig. 3e and Extended Data Fig. 9). Furthermore, the burden of rare, null GLP1R variants along with all rare GLP1R variants impairing Ca²⁺ mobilization, β-arr2 recruitment, cAMP pathway and/or cell surface expression strongly increased both HbA1c (P = 2.7×10⁻⁴ with a β of 0.98±0.27) and BMI levels (P = 9.9×10⁻⁴ with a β of 0.033±0.010) (Fig. 3e and Extended Data Fig. 9). These associations were even stronger when LoF variants of β-arr2 recruitment were excluded (P = 1.3×10⁻⁴ with a β of 1.2±0.30 and P = 7.2×10⁻⁴ with a β of 0.038±0.011, respectively) (Fig. 3e and Extended Data Fig. 9). This result suggested that defective β-arr2 recruitment is deleterious for glucose homeostasis and adiposity. Of note, we did not find any significant associations between rare deleterious GLP1R variants with EA score ≥ 60 and metabolic traits (Extended Data Fig. 9), highlighting the importance of in vitro analyses as we show here and in previous functional genetics-based studies,¹³, ¹⁴, ¹⁵ although the number of carriers was lower. Collectively, these results indicate that impaired GLP1R cell surface expression is a risk factor for increased
189 HbA1c, BMI and diastolic blood pressure levels. Impaired β-arr2 recruitment seems to have
190 rather a beneficial effect on these phenotypes, most likely by limiting GLP1R trafficking¹⁶.
191 We then measured incretin promoted glucose-stimulated insulin secretion (GSIS) in INS-1 823/3
192 (Glp1r KO) cells. Expression of WT GLP1R restored a functional response by Ex-4 (pEC₅₀ of
193 10.35 ± 0.28; n=4) and semaglutide (a clinically used GLP1R agonist¹⁷) (pEC₅₀ of 11.20 ± 0.38;
194 n=4) (Fig. 4a,b and Extended Data Fig. 10a,b). As expected, expression of mutants with LoF on
195 all pathways and severely impaired cell surface expression (i.e. p.H180Y, p.N320Y, p.G361R
196 and p.I400R) did not restore an Ex-4 response despite successful expression, even though lower
197 than for WT receptor (Fig. 4c,d, see also Fig. 2b). Expression of mutants in the categories
198 ‘Severely surface exp defective’ and ‘All pathways defective’ but with some residual activity on
199 the cAMP pathway (p.H173P, p.R310Q, p.R380C) did not elicit a response at a low Ex-4
200 concentration, considered as saturating for WT GLP1R (0.1 nM), and most likely not at
201 physiological GLP-1 concentraton. However, the same variants were fully responsive at 100 nM
202 Ex-4 (Fig. 4b, Fig. 4e-g). Similar rescue was observed for p.H173P with 100 nM semaglutide
203 (Fig. 4h). Positive allosteric modulators (PAM) are another potential way to improve the
204 defective response of LoF mutants to orthosteric ligands⁴. Co-stimulation of the p.R380C mutant
205 with 0.1 nM Ex-4 and the GLP1R PAM Compound 2 (10 µM)¹⁸, ¹⁹, ²⁰ restored a response similar
206 to the incubation with 100 nM Ex-4 alone (Fig. 4i). Compound 2 alone did not have a significant
207 effect on the p.R380C mutant (Fig. 4i). A similar pattern was observed for BETP (10 µM),
208 another GLP1R PAM, which was also effective on its own revealing its agonistic activity in
209 addition to its allosteric activity (Fig. 4j). Compound 2 and BETP similarly potentiated the
210 response of semaglutide at low concentrations (Fig. 4k,l). Mutants with defective β-arr2
211 recruitment showed WT-like GSIS (Extended Data Fig. 10c-f) indicating that defects in this
212 pathway do not inhibit GSIS. GoF mutants, either of the cAMP pathway alone (p.S261A) or in
213 combination with the Ca²⁺ pathway (p.Y291C, p.A316T) showed GSIS similar to WT GLP1R
214 and endogenous GIP receptors (Extended Data Fig. 4g-i) indicating that the improved signaling
215 had no notable consequences on GSIS in our experimental settings.

216 Taken together, in this study we discovered an unexpected high diversity and impact in terms of
217 functional properties in 56 out of 60 rare GLP1R mutants. Our results identify defective cell
218 surface expression and cAMP pathway activation as major determinants of GLP1R mutants for
219 defective insulin secretion. This defect can be recovered by two pharmacological paradigms
220 (higher agonist concentrations or a combination of low agonist concentration and allosteric
221 modulators) for some mutants. Carriers of these LoF GLP1R variants might thus not only benefit
222 from the latest generations of GLP1R agonists including unimolecular GLP1R/GIPR dual
223 agonists,²¹ but also from recently developed GLP1R positive allosteric modulators²², ²³. LoF
224 GLP1R variants were associated with impaired glucose homeostasis and increased adiposity.
225 Exclusion of LoF mutants for β-arr2 recruitment reinforced this association. This observation
226 supports the concept that β-arr-dependent internalization limits the action of GLP1R activation
227 on insulin secretion and suggests that carriers of LoF variants not associated with β-arr could
228 benefit from Gs-biased ligands²⁴.

229 This study has some limitations as we did not further explore the fact that rare GLP1R variants
230 are heterozygous and may either impact the phenotype through haplo-insufficiency or have a
231 dominant negative effect on the signalling by the co-expressed WT receptor. Aspects that should
232 be addressed in future studies are the demonstration that PAMs can improve the actions of
233 GLP1R agonists in GLP1R variant carriers, the impact of mutants on GLP1R signaling from
234 intracellular locations, on the recruitment of β-arr1, known to be also involved in insulin secretion
235 and β-cell apoptosis²⁵, ²⁶, and on physiological functions of GLP1R other than insulin secretion,
236 such as β-cell proliferation or inhibition of food intake¹.

237

238 ACKNOWLEDGMENTS
239 We thank Dr. J Naylor (Cambridge, UK) for kindly providing INS-1 832/3 (GLP1R KO) cells
240 and Dr. Mark Scott for giving advice for the selection of βarr-1/βarr-2 selective siRNA
241 sequences. This work was supported by the Fondation de la Recherche Médicale
242 (jfliu@mail.hust.edu.cn), Agence Nationale de la Recherche (ANR-2011-BSV1-012-01
243 "MLT2D", ANR-2011-META "MELA-BETES, ANR-21-CE18-0023 "alloGLP1R"), Institut
244 National de la Santé et de la Recherche Médicale (INSERM), Centre National de la Recherche
245 Scientifique (CNRS) and the "Who am I?" laboratory of excellence No.ANR-11-LABX-0071
246 funded by the French Government through its "Investments for the Future" program operated by
247 The French National Research Agency under grant No.ANR-11-IDEX-0005-01. This work was
248 supported by grants from the Ministry of Science and Technology (grant number
249 2018YFA0507003 and 2021ZD0203302 to J. L.), the National Natural Science Foundation of
250 China (NSFC) (grant numbers 81720108031, 81872945 and 31721002 to J. L.). This research
251 has been conducted using the UK Biobank Application #67575. This study was further funded
252 by the French National Research Agency (ANR-10-LABX-46 [European Genomics Institute for
253 Diabetes]), the French National Research Agency (ANR-10-EQPX-07-01 [LIGAN-PM]), the
254 European Research Council (ERC GEPIDIAB – 294785; ERC Reg-Seq – 715575), "France
255 Génomique" consortium (ANR-10-INBS-009) and the National Center for Precision Diabetic
256 Medicine - PreciDIAB, which is jointly supported by the French National Agency for Research
257 (ANR-18-IBHU-0001), by the European Union (FEDER), by the Hauts-de-France Regional
258 Council and by the European Metropolis of Lille (MEL). O.L. gratefully acknowledges support
259 from NIH GM066099. W.G. was supported by a doctoral fellowship from the Chinese
260 Scholarship Council (China).

261

262 AUTHOR CONTRIBUTIONS
W.G., L.L., R.S., A.B., J.L., and R.J. conceived and designed experiments. Z.F., and G.H. made constructions of variant plasmids and L.H. the non-tagged WT GLP1R plasmid. W.G., L.L., F.G., E.C., M.O., A.H. performed biochemical experiments. E.H. and O.L. did the clustering analysis. A.P. performed variant impact score analyses. A.B. and P.F. conceived and designed the next-generation sequencing study. A.B., M.D. and M.B. performed the genetic analyses. G.C., M.M., A.B., P.F. and B.B. contributed DNA samples from patients. W.G., L.L., A.B., O.L., J.D. and R.J. analyzed data. A.B., P.F., J.L., RJ obtained the funding. W.G., A.B., and R.J. wrote the manuscript that was edited and/or approved by all authors.

271

272 DECLARATION OF INTERESTS

273 The authors declare no competing interests
276 **Figure 1. Selection Process of GLP1R Variants and Expression of WT and Mutant GLP1R**
277 **in Cell Models.** a, Selection of 34 rare non-synonymous variants in GLP1R (NM_002062.5)
278 from ExAC browser and 25 rare and one frequent GLP1R variants from the RaDiO study¹⁰. EA,
279 evolutionary action algorithm; TM, transmembrane domain; ICD, intracellular domain. b,
280 Location of the 60 GLP1R variants. Mutant positions are labeled in red. The borders of the
281 membrane domain are delineated by the blue box. C-ter, carboxyl-terminal domain; e1 to e3,
282 extracellular loops 1 to 3; i1 to i3, intracellular loops 1 to 3; N-ter, amino-terminal domain. LoF,
283 loss-of-function; T2D, type 2 diabetes. c,d, Surface (Sur) and total (To) expression in HEK293T
284 and INS-1 823/3 (*Glp1r* KO) cells was determined by ELISA. (c) Expression of WT and mutant
285 GLP1R in HEK293T cells. Cell surface expression is shown at X-axis, total receptor expression
286 as color gradient and the Sur/To ratio as size of the bubble. Statistical significance of differences
287 (compared with WT GLP1R) was determined by one-way analysis of variance and Dunnett's
288 post-test. Sur: *P* < 0.05, **P* < 0.001, ***P* < 0.0001; Ratio: #P < 0.05, ##P < 0.001, ###P <
289 0.0001; Tot: (a) *P* < 0.05, (b) *P* < 0.001, (c) *P* < 0.0001. (d) Comparison of cell surface expression
290 of mutants in HEK293T and INS-1 823/3 (*Glp1r* KO) cells. Statistical significance of differences
291 between two cell types was determined by two-way analysis of variance and Sidak's multiple
292 comparisons test *P* < 0.05, **P* < 0.01, ***P* < 0.0001. 3-5 technical replicates of 3-13
293 independent biological replicates for each mutant; each mutant expressed as % WT. See also
294 Extended Data Fig. 2 and table S2 for complete data sets.
**Figure 2.** Functional Profiling of GLP1R Mutants Define Eight Categories. **a-g**, Ex-4 concentration-response curves of cAMP production, Ca²⁺ mobilization, ERK activation, and β-arr2 recruitment and radial graphs of one representative GLP1R mutant of each category. Mutant GLP1R (solid lines with filled circles) and WT GLP1R (dotted lines with open circles) were monitored in parallel in each experiment. For radial graphs, data were normalized to WT GLP1R (set as zero), values of mutants ranged from -1 to +1, where 0 to +1 represent enhanced properties, and 0 to -1 represents impaired properties. All values are means ± SEM of 2-3 technical replicates of 3-8 independent biological replicates for each mutant. Exp, expression; Δ, Δlog(τ/KA); Ex-4, Exendin-4. See also Extended Data Fig. 4 to Extended Data Fig. 7 and tables S2 and S3 for complete data sets for the agonist-mediated signaling activity of GLP1R mutants.

**Figure 3.** 56 Mutants Clustered into Three Groups are Correlated to the Level of Phenotypic Pb. a, Non-Negative Matrix Factorization (NMF) and K-means analysis clustered 56 mutants into 3 groups as shown in three dendrograms (red, blue, and black). The normalized difference values from phenotypic assays are represented in each radial plot and color-coded blue (Gain-of-Function, GoF) to red (Loss-of-Function, LoF). Phenotype scores were set from -1 to +1. WT GLP1R was set as zero, values of mutants ranging from 0 to +1 represent enhanced properties, and from 0 to -1 impaired properties. **b**, The box plot shows the distribution of the mutants into three clusters based on their phenotype score defined in the ‘Methods’ section. **c**, Superimposed radial graphs of mutants belonging to the same cluster. Cluster 1 is characterized by a complete loss of β-arr2 response and also drastically reduced potency of the cAMP response. They also lost mid to high ERK efficacy. Cluster 2 shows detectable β-arr2 function but drastic losses in Emax and log(τ/KA). These mutants also have reduced ERK efficacy but increased ERK potency. Member of Cluster 3 shows
lower phenotype scores than those of the other two clusters. **d**, The predictive evolutionary Action (EA) score of GLP1R mutants in the TM domain is correlated with the experimentally determined Phenotypic score of these mutants. R²=0.41 for the linear correlation (*P* < 0.0001). **The TM domain was selected because of its highest predictive value for GPCRs²⁷**, Pb, Perturbatio. **e**, Association between rare GLP1R variants and metabolic traits in the UK Biobank. β-arr2, beta arrestin 2; BMI, body mass index; DBP, diastolic blood pressure; HbA1c, glycated hemoglobin A1C; HDL, high-density lipoprotein; LDL, low-density lipoprotein; SBP, systolic blood pressure; SE, standard error.

329

Figure 4. Rescue of Insulin Secretion of GLP1R Mutants Expressed in INS-1 823/3

(Glp1r KO) cells. INS-1 823/3 (Glp1r KO) pancreatic β-cell line deleted of its Glp1r gene was used to examine the capacity of GLP1R mutants to promote glucose-stimulated insulin secretion. **a**, Ex-4 (100 nM) and GIP (100 nM) response in mock-transfected cells. **b**, Ex-4 concentration-response curve in cells expressing GLP1R WT. **c**, Total expression of mutants determined by ELISA. **d-g**, Ex-4 response in cells expressing mutants with (d,e) severely defective cell surface expression or (f,g) severely defective cAMP pathway (2 logs right shifted EC₅₀). **h**, Semaglutide response in cells expressing WT GLP1R, p.H173P, p.R310Q or **p.R380C mutants**. **i,j**, Ex-4 response in the presence of Compound 2 or BETP in cells expressing the p.R380C mutant. **k,l**, Semaglutide response in the presence of Compound 2 or **BETP in cells expressing the p.R380C mutant**. Responses are normalized to glucose-induced insulin secretion in the absence of Ex-4. All values are means ± SEM of at least three independent experiments. Statistical significance of differences (compared with control) was determined by one-way analysis of variance and Dunnett's post-test *P* < 0.05, **P** < 0.01, ***P* < 0.0001. Statistical significance of differences (compared with 0.1 nM treatment of GLP1R mutant) was determined by one-way analysis of variance and Dunnett's post-test #P
346 < 0.05, ###P < 0.0001. Ex-4, Exendin-4; G-ctrl, glucose control; Comp 2, Compound 2;

347 Sema, Semaglutide.

348
349 **METHODS**

350 **Studies in cellular models**

351 HEK293T cells (RRID: CVCL 0063) were cultured in Dulbecco's modified Eagle's medium
352 (DMEM, GIBCO, 10566) consisting of 10% fetal bovine serum (FBS), 100 U/ml penicillin, and
353 0.1 mg/ml streptomycin. INS-1 832/3 cells lacking endogenous Glp1r after deletion by CRISPR-
354 Cas9 ¹¹, a gift from Dr Jacqueline Naylor, were cultured in RPMI-1640 medium (Invitrogen),
355 supplemented with 10% FBS, 100 U/ml penicillin, 0.1 mg/ml streptomycin, 1 mM sodium
356 pyruvate, 10 mM HEPES and 50 µM 2-mercaptoethanol. Cells were incubated in a humidified
357 air incubator containing 5% CO2 at 37°C.

358 **GLP1R gene sequencing**

359 Participants included in the RaDiO study were previously described (Nat Med. 2019
360 Nov;25(11):1733-1738. // Nat Metab. 2020 Oct;2(10):1126-1134.). DNA sequencing of GLP1R
361 (NM_002062.5) was performed by next-generation sequencing as previously described (Nat
362 Med. 2019 Nov;25(11):1733-1738. // Nat Metab. 2020 Oct;2(10):1126-1134.). Briefly,
363 NimbleGen SeqCap EZ Choice XL target enrichment (Roche, Pleasanton, USA) was performed
364 according to the manufacturer's protocol for next-generation sequencing on the HiSeq 4000
365 system (Illumina, San Diego, USA), using a paired-end 2×150 bp protocol. The demultiplexing
366 of sequence data was performed using bcl2fastq Conversion Software (Illumina; v2.17).
367 Sequence reads were then mapped to the human genome (hg19/GRCh37) using Burrows-
368 Wheeler Aligner (v0.7.13). The variant calling was performed using Genome Analysis ToolKit
369 (GATK; v3.3). Only variants with a coverage higher than 8 reads were kept for further analyses.
370 The annotation of variants was performed using the Ensembl Perl Application Program Interfaces
371 (v75) and custom Perl scripts to include data from both dbSNP (version 135) and dbNSFP (v3.0)
372 databases. All coding variants had a QUAL score higher than 50. Furthermore, no variant had
more than 5% missing genotype (with a coverage below 8 reads or a QUAL score below 50) across the participants.

In UK Biobank (Application #67575), we analyzed up to 187,743 samples, with available exome sequencing data and clinical data. More specifically, we used exome data from pVCF format (field #23156). Only variants with a coverage higher than 10 reads and quality GQ score higher than 20 were kept for further analyses. Annotation of variants in GLP1R (NM_002062.5) was done using the Ensembl Variant Effect Predictor (VEP) tool version 103 (RefSeq). Subsequently, the analysis was focused on loss-of-function variants. No loss-of-function variant had more than 5% missing genotype (i.e. with a coverage below 10 reads or a GQ score below 20) across the participants.

### Selection of GLP1R coding variants for functional in vitro analysis

In 2016, the ExAC browser (previous version of Genome Aggregation Database [GnomAD]) included 132 nonsynonymous variants in GLP1R (NM_002062.5), including five common variants with a MAF higher than 1% (Fig. 1 and table S1). To predict the functional impact of these variants in silico, we determined their evolutionary action (EA) score 7 (Extended Data Fig. 1). The EA has been shown to usefully predict the functional impact of mutations in genes encoding GPCRs 14, 27. It takes into account the relative importance of each residue position estimated with the evolutionary trace method based on phylogenetic divergences 8, combined with the likelihood to observe a given amino acid substitution at that position in receptor homologs across evolution 7. We selected 44 missense GLP1R variants predicted to be of moderate to high impact based on their EA scores. Available literature data on the functional consequences of alanine mutations at 11 positions among the positions of the 132 variants guided us further in the selection of the most impactful variants (Fig. 1). To further narrow down the number of variants we focused on mutations located in the TM and intracellular domains, both known to be important for receptor activation and signal transduction. At the end this selection
process, we focused on 34 rare variants with high predicted functional impact (Fig. 1, Extended Data Fig. 1a and table S1). In parallel, we performed sequencing of GLP1R exons (NM_002062.5) in 8,672 participants from the RaDiO study¹⁰. We identified 46 nonsynonymous variants of which we selected 25 rare variants and a common one encoding p.A316T because of their high predicted functional impact (Fig. 1, Extended Data Fig. 1b and table S1). In total, 60 GLP1R variants were selected for *in vitro* functional analyses (see Fig. 1b for positions in the receptor).

### Receptor mutagenesis and constructs

GLP1R cDNA construct containing an N-terminal SNAP tag fused to a FLAG tag were obtained from Cisbio Bioassays (Codolet, France). GLP1R mutants were generated by site-directed mutagenesis using QuikChange Lightning Site-Directed Mutagenesis Kit (Agilent Technologies, 210518) according to the manufacturer's protocols. The non-tagged GLP1R was generated by replacing the SNAP-flag cassette and by an oligonucleotide reconstituting the N-terminal methionine residue. All constructs were verified with Eurofins sequencing.

### Transfection of plasmids and siRNA

HEK293T cells were transiently transfected with plasmid DNA by the reagent JetPEI (101-10N, Polyplus, New York, NY, USA) and transfected with siRNA using INTERFERin® (101000028, Polyplus, Illkirch, FRANCE) according to the manufacturer's instructions. INS-1 832/3 (*Glp1r* KO) cells were transiently transfected with Lipofectamine® LTX & Plus Reagent (15338-100, Invitrogen) according to the manufacturer's instructions. Generally, cells were 50-70% confluent at the time of transfection. At least forty-eight hours after transfection, both HEK293T and INS-1 832/3 (*Glp1r* KO) cells were experimentally manipulated for all the ELISA and signaling assays. The double-stranded 5'-ACCUGCGCCUUCCGCUAUG-3' siRNA sequence (Eurogentec) was used to simultaneously target both βarr-1 and βarr-2, as described previously²⁸.
423 **Cell surface and total receptor expression**

424 HEK293T and INS-1 832/3 (Glp1r KO) cells were transfected with GLP1R or mutant receptor
425 cDNA construct containing an N-terminal SNAP tag fused to a FLAG tag. After 24h, the cells
426 were seeded into 96-well white Optiplates (6005680, Perkin Elmer) and cultured overnight at
427 37°C in 5% CO2. To measure the surface expression, the ELISA cells were washed with 1x PBS
428 and fixed with 2% paraformaldehyde (PFA) at room temperature for 10 min. For total receptor
429 measurement, cells washed with 1x PBS and fixed with methanol/acetone (1: 1) at room
temperature for 1 min and then additionally treated with 0.2% Triton X-100 at room temperature
430 for 10 min. The cells are blocked over 1 hour by 3% BSA for surface expression and 3% BSA
431 containing 0.2% Triton X-100 for total expression. Receptor expression was then measured using
432 a rabbit anti-flag antibody (F7425, Sigma-Aldrich) and a horseradish peroxidase-conjugated
433 rabbit immunoglobulin G (IgG) secondary antibody (Cell signaling, 7074S). Luminata™ Forte
434 ELISA HRP substrate (ELLUF0100, Merck Millipore) was used for the reaction to generate
435 luminescence. Luminescence was read with a Tecan Infinite M500 microplate reader (Tecan
436 Group, Ltd., Männedorf, Switzerland). No interference of the N-terminal SNAP-flag-tag was
437 observed as similar results were observed with the non-tagged and the SNAP-flag-tagged WT
438 GLP1R in INS-1 823/3 (Glp1r KO) and HEK293T cells (Extended Data Fig. 3g-j).
439 For internalization assays cells are incubated with 100 nM exendin-4 (Bachem, Weil am Rhein,
440 Germany) at 37°C in 5% CO2 for the indicated times. The amount of surface and total receptors
441 were then determined by ELISA.

442 were then determined by ELISA.

443 **LUXendin Flow cytometry**

12 week-old C57/BL6 (Janvier, France) male mouse islet isolation was performed as described
444 previously²⁹. Islets were cultured in RPMI 1640 (#61870-010, Thermo Fisher Scientific)
445 containing 10% fetal calf serum (FCS CVFSVF00-01, Eurobio, Les Ulis, France) and
446 penicillin/streptomycin (#15140122, ThermoFisher Scientific) at 37°C, 5% CO2. Islets were
447
448 incubated with 100 nM of LUXendin¹² (Celtarys CELT111), or with 10 µM Exendin-4 (Bachem,
449 Weil am Rhein, Germany) for 1h. Islets were then dissociated in single cell suspensions using
450 Accutase (#07922, Stemcell technologies, Vancouver, Canada). GLP1R or Mock transfected
451 INS-1 832/3 (Glp1r KO) and HEK293T were incubated with 100 nM of LUXendin for 1h and
detached with trypsin. Cell sorting was carried out using a FACSAria III (BD Bioscience). Data
452 were analyzed using FlowJo™ Software (RRID:SCR_008520, BD Life Sciences). LUXendin-
453 positive cells were sorted in several sequential steps as described in Supplementary Figure 1. Data
454 were normalized by substracting background staining (Mock transfected INS-1 832/3 (Glp1r
455 KO) and HEK293T or Exendin-4 excess (GLP1R+ beta-cells) and are expressed as Mean
456 Fluorescent Intensity (MFI) per cell.
457

458

459 **cAMP accumulation measurement**

460 Ligands-mediated cAMP accumulation assays were performed using the cAMP Gi kit
461 (62AM9PEB, Cisbio Bioassays) as previously described³⁰. Cells transiently expressed GLP1R
462 WT or mutants. Forty-eight hours post-transfection, cells were suspended in stimulation buffer
463 from kit and distributed to a 384-well white ProxiPlate (6008280, Perkin Elmer) at a density of
464 7500 cells per well. Increasing concentration of ligands was added to cell suspension. After
465 30min stimulation, cAMP d2 antibody and cAMP Eu-cryptate reagent were added. After one
466 hour of stimulation, cAMP measurements were performed in triplicates and were read in Tecan
467 Infinite M500 microplate (Tecan Group, Ltd., Männedorf, Switzerland).

468 **ERK activation measurement**

469 Intracellular phospho-ERK1/2 was measured using the AlphaLISA Surefire pERK kit as
470 described previously³¹ (ALSU-PERK-A500, PerkinElmer, Waltham, MA). HEK293T cells
transiently expressed GLP1R WT or one of the 60 GLP1R mutants. The cells are starved
471 overnight prior to stimulation. An increasing concentration of ligands diluted in DMEM
472
473 (Invitrogen) free FBS, was added at 37°C for the indicated times to generate full concentration-
474 response curves. Cellular lysates were generated by adding the lysis buffer. Four µl cellular
475 lysates were transferred to a 384-well white ProxiPlate (6008280, Perkin Elmer). After the
476 reaction mixture was added and the signal was detected using the Tecan Infinite M1000 PRO
477 microplate reader (Tecan Group, Ltd., Männedorf, Switzerland) with excitation at 680nm (α-
478 laser) and emission at 520-620nm.

479 Exendin-4 induced ERK1/2 phosphorylation kinetics was determined over 1 h. At 5min, the
480 exendin-4-mediated pERK1/2 was maximal for HEK293T cells. Accordingly, pERK1/2 dose-
481 response experiments were performed at 5 min. At 5 min the Gs/cAMP/PKA pathway was the
482 predominant input pathway (Extended Data Fig. 3k-n).

483

484 **Intracellular calcium mobilization measurement**

485 Intracellular Ca²⁺ mobilization detected in HEK293T cells was performed as previously
486 described. Briefly, cells were pre-incubated with the Ca²⁺-sensitive Fluo-4 AM (Thermo Fisher
487 Scientific) in 37°C incubator for 1 h before measuring in the multi-mode microplate reader
488 (FlexStation 3, Molecular Devices). The fluorescence signals (excitation at 485 nm and emission
489 at 525 nm) were then measured for 60 s. After the first 20 s, compounds were added automatically
490 into the plate to treat the cells. The Ca²⁺ response was given as the agonist-induced fluorescence
491 increase (maximum signal after agonist addition subtracts the mean value of the first 20 s). The
492 dependence of the Ca response on Gq/11 proteins was addressed by preincubating cells for 30
493 min with the Gq/11 protein specific YM-254890 inhibitor in the presence of Ex-4 (100 nM)
494 (Extended Data Fig. 3o).

495 β-arr2 recruitment (BRET) measurement

496 β-arr2 recruitment by GLP1R at the cell surface was assessed by measuring BRET between
497 RlucII-β-arr2 and rGFP-CAAX (prenylation CAAX box of KRas) upon treatment of HEK 293T
cells cotransfected with GLP1R. Transfected cells were plated in 96-well white Optiplates (6005680, Perkin Elmer). Forty-eight hours after transfection, cells were washed with Dulbecco's phosphate-buffered saline, and then Tyrode's buffer was added. After 5 min incubation with Deep blue C Coelenterazine (2.5 µM, NanoLight Technology), the cells were incubated for 5 more minutes with exendin-4 at 37°C. Then, luminescence and fluorescence were measured simultaneously using plates and were read on the Mithras LB 940 with 480 ± 10 nm (Rluc) and 540 ± 20 nm (YFP) emission filters and BRET ratios were calculated.

## Insulin secretion measurement

INS-1 832/3 (Glp1r KO) cells were seeded into 24-well plates coated with poly-L-lysine hydrobromide (P6282, Sigma-Aldrich). GLP1R or one of the 60 GLP1R mutants were transfected one day after. The cultured medium was changed by fresh cultured medium 24 h prior to glucose-dependent insulin secretion. On the day of the experiment, the cells were washed three times by low-glucose (2.8 mM) Krebs Ringer buffer (2.6 mM CaCl2, 98.5 mM NaCl, 4 mM KCl, 1.2 mM KH2PO4, 1.2 mM MgSO4, 20 mM HEPES, 25.9 mM NaHCO3, 0.2% BSA, pH 7.4) and incubated for 1 h at 37°C in low-glucose (2.8 mM) Krebs Ringer buffer. The supernatant was removed, and cells were incubated for 1 h at 37°C in high-(8.3 mM) glucose Krebs Ringer buffer ± exendin-4 or GIP or semaglutide ¹¹. The supernatant was collected and insulin concentration was measured in 10 µL using the Insulin Ultra Sensitive assay (62IN2PEG, Cisbio Bioassays). According to the manufacturer's instructions, supernatant, insulin Eu³⁺ Cryptate antibody and insulin XL665 antibody were distributed in a 384-well microplate (6007290, Perkin Elmer). After 24 hours incubation, the signal was read in Tecan Infinite M500 microplate (Tecan Group, Ltd., Männedorf, Switzerland).

## TR-FRET-based ligand competition binding measurement

The affinity of GLP1R WT and GLP1R mutants for exendin-4 were determined by TR-FRET-based ligand competitive binding assay. Forty-eight hours post-transfection, HEK293T cells
523 expressing SNAP-GLP1R WT or mutants were immediately placed on the ice to avoid the rapid
524 receptor internalization. After washes, the cells were incubated with substrate (100 nM)
525 conjugated to the long-lived fluorophore Terbium cryptate (Tb; Lumi4-Tb, SSNPTBX, Cisbio
526 Bioassays) in Tag-lite labeling medium (1 h, on ice, LABMED, Cisbio Bioassays). After several
527 washes, cells were dissociated by enzyme-free cell dissociation buffer (C5789; Sigma-Aldrich)
528 and resuspended in Tag-lite buffer. The cells are distributed into a 384-well plate, whose then
529 were used to detect fluorescence signal at 620 nm for verification of the efficiency of fluorescent
530 labeling of SNAP. An increasing concentration of exendin-4 was incubated with cells in the
531 presence or absence of the exendin-4 derivative labeled with a red-emitting HTRF fluorescent
532 probe (L0030RED, Cisbio Bioassays) at final reaction volume of 14 µL. The incubation last two
533 hours at room temperature and the TR-FRET signal was read in the Tecan Infinite M500
534 microplate reader (Tecan Group, Ltd., Männedorf, Switzerland) following settings: excitation at
535 340 nm (Tb, energy donor), emission at 665 nm (d2, acceptor); and 620 nm (donor); delay of
536 150 µs; and integration time of 500µs. Data is expressed as TR-FRET ratio (acceptor/donor) or
537 normalized as % when indicated (maximal TR-FRET ratio = 100%, non-specific binding = 0%).

538 *Western blotting*

539 HEK293T cells were seeded in 6-well plates and transiently expressed GLP1R and silenced by
540 using siRNA targeting both β-arr1 and β-arr2 according to the manufacturer's instructions. The
541 cells were then washed with PBS carefully. Lysis buffer composed of 62.5mM Tris/HCl pH 6.8,
542 5% SDS, 10% glycerol, 0.005% bromophenol blue are applied to denature proteins in cells over
543 2 hours. Samples were then sonicated for 5s, three times, and heated for 5 min at 95 °C. Denatured
544 protein samples were resolved in SDS-PAGE and then transferred to nitrocellulose membranes.
545 The immunoblottings were carried out with primary antibodies against the Flag tag (F7425,
546 Sigma-Aldrich) and β-arr1/2 (4674, Cell Signaling Technology). Immunoreactivity was revealed
547 using a secondary antibody coupled to 680 or 800 nm fluorophores (LI-COR Biosciences,
548 Lincoln, NE, USA), and readings were performed with the Odyssey LI-COR infrared fluorescent scanner (LI-COR Biosciences).

550 NMF/K-mean Clustering Analysis

551 To characterize the phenotypic effects of the GLP1R mutants, we applied the Non-Negative 552 Matrix Factorization (NMF) and K-means clustering analysis described in 27. Among the 60 553 mutants tested on GLP1R, four mutants (p.H180Y, p.N320Y, p.G361R, and p. I400R) were 554 excluded because their experimental data were undetectable. To initiate the clustering, an input 555 matrix was generated with 56 mutants and 4 different signaling pathways (β-arr2, Ca2+, cAMP, 556 and ERK) measured by 3 parameters each (Emax, EC50, and Δlog(τ/KA)), which resulted in matrix 557 size of 56 x 12. To establish the robustness of the results, experimental errors were propagated 558 by iteratively sampling values within one standard deviation of the mean of the phenotypic 559 measurement. This generated a background of 300 input matrices that were independently 560 processed by NMF/K-mean clustering. Before applying the clustering algorithm, each 561 phenotypic measurement was normalized against WT:

562 Normalized Difference Value_{ij} = \frac{x_{ij} - WT_{j}}{x_{ij} + WT_{j}} + 1 (1),

563 where xij indicates the j phenotypic measurement on mutant i, and WTj indicates wild type values 564 on the j phenotypic measurement. Therefore, each value ranged from 0 to 2, where 1 indicates 565 an activity similar to WT. NMF was performed in the normalized matrix from 566 sklearn.decomposition package in python to reduce dimensionality [K (basis factor) x H (number 567 of mutants)]. We applied K-means analysis to the result of dimension reduction, using the 568 sklearn.cluster package in python, across K=2 to K=5, where K is basis factor for NMF and the 569 number of clusters for K-means (KNMF=KKmean). For each input matrix, NMF/K-means was 570 iteratively applied 300 times. Thus, the final clustering frequency was determined by averaging 571 90,000 outcomes (300 input matrix times 300 clustering iteration) and converted into Euclidean 572 distance matrix, using the scipy.cluster package in python.
573 Evolutionary Action Scores

574 The Evolutionary Action (EA) of a mutation is computed with an equation 7:

575 $d\phi = \nabla f \cdot d\gamma$. (2),

576 where f is a fitness function that maps genotypes, γ, to phenotypes, φ, so that we may write
577 $f(\gamma) = \phi$. In practice, Eqn 2 can be computed by estimating $d\phi$ as the magnitude of a mutation
578 from evolutionary odds matrices of amino acid substitutions, and estimating $\nabla f$, which as the
579 gradient of the evolutionary function represent the functional sensitivity to mutations at each
580 sequence positions, with the Evolutionary Trace 8. The result is the EA, $d\phi$, which varies
581 continuously from 0 (a neutral mutation with no fitness effect) to 100 (a maximally deleterious
582 mutation that causes a functional knockout). EA scores below 30 tend to be harmless, but tend
583 to impact function progressively more above that threshold. The GLP1R mutants EA scores were
584 given from http://eaction.lichtargelab.org/eaction. To evaluate EA score prediction with the
585 experimental data, phenotypic score was calculated thus:

586 Phenotypic Score<sub>i</sub> = $\sum_{j=0}^{n} |y_{ij}|$

587 $y_{ij} = \frac{x_{ij} - WT_j}{x_{ij} + WT_j}$,

588 Statistical analysis

589 Statistical analyses for genetic association studies. In UK Biobank, the rare variants were
590 analyzed as single clusters using the mixed-effects score test (MiST) method (Sun, J., Zheng, Y.
591 & Hsu, L. A unified mixed-effects model for rare-variant association in sequencing studies.
592 *Genet. Epidemiol.* **37**, 334–344 (2013)). MiST provides a score statistic $S(\pi)$ for the mean effect
593 ($\pi$) of the cluster, and a score statistic $S(\tau)$ for the heterogeneous effect ($\tau$) of the cluster. Let the
594 equation of the model be: $Y = \alpha X + \pi GZ$, where Y is the trait of interest, X is the matrix of
595 covariates (i.e. age, sex, body mass index [BMI], ancestry [i.e. PC1 to PC5; field #22009] for
596 assessing diastolic blood pressure, systolic blood pressure, high-density lipoprotein, low-density
597 lipopretin and age, sex, ancestry for assessing BMI and glycated hemoglobin A1c), G is the
598 matrix of *OPRD1* variants and Z is a vector of ones repeated *n* times, with *n* the number of rare
599 *OPRD1* variants, leading to: $πGZ = π \sum_{i=1}^{n} G_i$. BMI was log-transformed before analysis. As
600 none of the association studies had significant heterogeneity, we only showed the *P*-values
601 associated with the mean effect ($π$) of the cluster. These statistical analyses were performed using
602 R software (v4.0.2).

603 **The surface and total expression determined by ELISA.** All values are expressed as means ±
604 SEM of at least three independent experiments. Statistical significance of differences was
605 determined by one-way analysis of variance and Dunnett's post-test.

606 **Insulin secretion measurement.** The agonist-induced response for every GLP1R mutant was
607 normalized to its glucose control (set at 1). The fold ratio is expressed as means ± SEM of at least
608 three independent experiments and compared to the WT receptor in parallel with the receptor
609 mutant. Statistical significance of differences was determined by one-way analysis of variance
610 and Dunnett's post-test. LogEC₅₀ is defined as the log of the concentration of initiating half of
611 the maximal response was determined by nonlinear regression with a variable Hill slope using
612 GraphPad Prism software (version 7.0).

613 **TR-FRET-based ligand competition binding measurement.** LogIC₅₀ is defined as the log of the
614 concentration of red-emitting Ex-4 that results in half-way of decreasing of Ex-4 binding. logIC₅₀
615 was determined by nonlinear regression with a variable Hill slope using GraphPad Prism
616 software (version 7.0). LogIC₅₀ is expressed as means ± SEM of at least three independent
617 experiments. The data were analyzed by comparing independent fits with a global fit that shares
618 the selected parameter and by two-way analysis of variance and Sidak post-test.

619 **cAMP accumulation, ERK activation, Ca2+ mobilization and β-arr2 recruitment**
620 **measurement.** Agonist-induced Emax is defined as the maximal response generated by agonists.
621 LogEC₅₀, and agonist-induced Eₘₐₓ values were determined by nonlinear regression with a
622 variable Hill slope using GraphPad Prism software (version 7.0).

623 For these assays, the agonist-induced E<sub>max</sub> value for every GLP1R mutant was normalized as a
624 percentage of the maximal Ex-4 stimulated response of the WT receptor (set at 100) monitored
625 in parallel with the receptor mutant. LogEC<sub>50</sub> and agonist-induced E<sub>max</sub> are expressed as means
626 ± SEM of at least three independent experiments. The data were analyzed by comparing
627 independent fits with a global fit that shares the selected parameter and by two-way analysis of
628 variance and Sidak post-test. The concentration-response curves were fitted to an operational
629 model of agonism designed by Kenakin and Christopoulos <sup>32, 33</sup> to obtain log(τ/K<sub>A</sub>) values for
630 the WT receptor and its mutants. Normally, an agonist is set as a reference agonist, against which
631 within pathway comparisons for the same receptor to other agonists can be made and expressed
632 as Δlog(τ/K<sub>A</sub>). Here, withinpathway comparisons were made between GLP1R mutants and the
633 WT receptor. Normalized difference was calculated on values corresponding to agonist-induced
634 E<sub>max</sub>, and Δlog(τ/K<sub>A</sub>) to fit a -1 to +1 scale using the following formula: (mutant - WT)/(mutant
635 + WT). In the case of Δlog(τ/K<sub>A</sub>), before normalization, the antilogs were first calculated and
636 then were fitted to the following formula: (mutant - WT)/(mutant + WT). Positive and negative
637 values represent mutations with better or worst responses, respectively than those of the WT
638 receptor. Subsequently, Δlog(τ/K<sub>A</sub>) values were expressed as means ± SEM of the indicated
639 number of experiments (n). Statistical analysis for Δlog(τ/K<sub>A</sub>) ratios was performed by one-
640 sample t test to examine the mean differences between WT GLP1R and its mutants.

641 All the correlation studies are analyzed by linear regression and define R² using GraphPad Prism
642 software (version 7.0). The statistical significance of differences was determined by linear
643 regression.

644
645 Further information and requests for resources and reagents should be directed to and will be

646 fulfilled by the Lead Contact, Ralf Jockers (ralf.jockers@inserm.fr)

647

648 REFERENCES

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761

762
<figure><img src="image_2.png" /><figcaption>763 **Figure 1**</figcaption></figure>
<figure><img src="image_3.png" /></figure>
<figure><img src="image_4.png" /><figcaption>768 Figure 3</figcaption></figure>

<figure><img src="image_5.png" /></figure>

<table><thead><tr><th>Trait</th><th>Impaired pathway</th><th>N<sub>variants</sub></th><th>Sample size</th><th>Beta</th><th>SE</th><th>p-value</th></tr></thead><tbody><tr><td>HbA1c</td><td>Surface expression</td><td>16</td><td>186517</td><td>0.95</td><td>0.28</td><td>6.9 x 10<sup>-4</sup></td></tr><tr><td>HbA1c</td><td>Surface expression + null</td><td>35</td><td>186517</td><td>0.98</td><td>0.27</td><td>2.8 x 10<sup>-4</sup></td></tr><tr><td>HbA1c</td><td>All</td><td>36</td><td>186517</td><td>0.98</td><td>0.27</td><td>2.7 x 10<sup>-4</sup></td></tr><tr><td>HbA1c</td><td>All except β-arr2 recruitment</td><td>26</td><td>186517</td><td>1.2</td><td>0.30</td><td>1.3 x 10<sup>-4</sup></td></tr><tr><td>BMI</td><td>Surface expression</td><td>16</td><td>187743</td><td>0.032</td><td>0.011</td><td>2.6 x 10<sup>-3</sup></td></tr><tr><td>BMI</td><td>Surface expression + null</td><td>35</td><td>187743</td><td>0.034</td><td>0.010</td><td>8.7 x 10<sup>-4</sup></td></tr><tr><td>BMI</td><td>All</td><td>36</td><td>187743</td><td>0.033</td><td>0.010</td><td>9.9 x 10<sup>-4</sup></td></tr><tr><td>BMI</td><td>All except β-arr2 recruitment</td><td>26</td><td>187743</td><td>0.038</td><td>0.011</td><td>7.2 x 10<sup>-4</sup></td></tr><tr><td>DBP</td><td>Surface expression</td><td>16</td><td>177328</td><td>1.3</td><td>0.62</td><td>0.044</td></tr><tr><td>DBP</td><td>Surface expression + null</td><td>34</td><td>177328</td><td>1.4</td><td>0.60</td><td>0.023</td></tr><tr><td>DBP</td><td>All</td><td>35</td><td>177328</td><td>1.3</td><td>0.60</td><td>0.029</td></tr></tbody></table>
<figure><img src="image_6.png" /></figure>
a

<figure><img src="image_7.png" /></figure>

ExAC browser:

132 non-synonymous variants

<figure><img src="image_8.png" /></figure>

<figure><img src="image_9.png" /></figure>

Literature data
(LoF)

<figure><img src="image_10.png" /></figure>

Prediction of
impactfulness of
variants
(EA Score):

<figure><img src="image_11.png" /></figure>

Topology:
TM and ICD

<figure><img src="image_12.png" /></figure>

b

<figure><img src="image_13.png" /></figure>

c

<figure><img src="image_14.png" /></figure>

d

<figure><img src="image_15.png" /></figure>
Severely surface exp defective

<figure><img src="image_16.png" /></figure>

All pathways defective

<figure><img src="image_17.png" /></figure>

Two or three pathways defective

<figure><img src="image_18.png" /></figure>

β-arr2 specific defective

<figure><img src="image_19.png" /></figure>

ERK specific defective

<figure><img src="image_20.png" /></figure>

cAMP Gain of function

<figure><img src="image_21.png" /></figure>

Ca²⁺ Gain of function

<figure><img src="image_22.png" /></figure>

Wild-type like

<figure><img src="image_23.png" /></figure>
a

<figure><img src="image_24.png" /></figure>

b

<figure><img src="image_25.png" /></figure>

c

Cluster 1

<figure><img src="image_26.png" /></figure>

Cluster 2

<figure><img src="image_27.png" /></figure>

Cluster 3

<figure><img src="image_28.png" /></figure>

d

<figure><img src="image_29.png" /></figure>

e

<table><thead><tr><th>Trait</th><th>Impaired pathway</th><th>N<sub>variants</sub></th><th>Sample size</th><th>Beta</th><th>SE</th><th>p-value</th></tr></thead><tbody><tr><td>HbA1c</td><td>Surface expression</td><td>16</td><td>186517</td><td>0.95</td><td>0.28</td><td>6.9 × 10<sup>-4</sup></td></tr><tr><td>HbA1c</td><td>Surface expression + null</td><td>35</td><td>186517</td><td>0.98</td><td>0.27</td><td>2.8 × 10<sup>-4</sup></td></tr><tr><td>HbA1c</td><td>All</td><td>36</td><td>186517</td><td>0.98</td><td>0.27</td><td>2.7 × 10<sup>-4</sup></td></tr><tr><td>HbA1c</td><td>All except β-arr2 recruitment</td><td>26</td><td>186517</td><td>1.2</td><td>0.30</td><td>1.3 × 10<sup>-4</sup></td></tr><tr><td>BMI</td><td>Surface expression</td><td>16</td><td>187743</td><td>0.032</td><td>0.011</td><td>2.6 × 10<sup>-3</sup></td></tr><tr><td>BMI</td><td>Surface expression + null</td><td>35</td><td>187743</td><td>0.034</td><td>0.010</td><td>8.7 × 10<sup>-4</sup></td></tr><tr><td>BMI</td><td>All</td><td>36</td><td>187743</td><td>0.033</td><td>0.010</td><td>9.9 × 10<sup>-4</sup></td></tr><tr><td>BMI</td><td>All except β-arr2 recruitment</td><td>26</td><td>187743</td><td>0.038</td><td>0.011</td><td>7.2 × 10<sup>-4</sup></td></tr><tr><td>DBP</td><td>Surface expression</td><td>16</td><td>177328</td><td>1.3</td><td>0.62</td><td>0.044</td></tr><tr><td>DBP</td><td>Surface expression + null</td><td>34</td><td>177328</td><td>1.4</td><td>0.60</td><td>0.023</td></tr><tr><td>DBP</td><td>All</td><td>35</td><td>177328</td><td>1.3</td><td>0.60</td><td>0.029</td></tr></tbody></table>
a INS-1 823/3 (Gly1r KO)

<figure><img src="image_30.png" /></figure>

b

<figure><img src="image_31.png" /></figure>

c

<figure><img src="image_32.png" /></figure>

d

<figure><img src="image_33.png" /></figure>

e

<figure><img src="image_34.png" /></figure>

f

<figure><img src="image_35.png" /></figure>

g

<figure><img src="image_36.png" /></figure>

h

<figure><img src="image_37.png" /></figure>

i

<figure><img src="image_38.png" /></figure>

j

<figure><img src="image_39.png" /></figure>

k

<figure><img src="image_40.png" /></figure>

l

<figure><img src="image_41.png" /></figure>